The Tech Trends You Need To Know For 2017: FTI's Annual Report

1. 1 2017 Tech Trend Report Emerging technology trends that will inﬂuence business, work, politics, government, media, education, and society in the coming year.

2. A great wave of disruption—anchored in artificial intelligence, robotics, self-driving cars, genomic editing, cognitive computing, the Internet of Things, and big data—is underway. As these technologies move from the fringe to the mainstream, they promise to forever change how we live, work and play. The 2017 Tech Trends Report, now in its 10th year, focuses on mid- to late-stage emerging technologies that are on a growth trajectory. We have identified more than 150 trends for the coming year across numerous industries, and our broad scope was intentional. In this era of rapidly accelerating technological advancement, changes within one industry necessarily impact another. We listen to signals across different sectors, and we encourage you to do the same. Now more than ever, organizations must examine the potential impact of tech trends. Whether you are a Fortune 500 company, a government agency, a startup, a university, a foundation or a small business, you must factor the trends in this report into your strategic thinking for the coming year, and adjust your planning, operations and business models accordingly. Failing to track trends in a meaningful way will put your competitive advantage and growth at risk. This is a robust, detailed document—don’t try to read it in one sitting. Start with the executive summary, and read through the top trends listed for your industry. In the coming weeks, spend some time with all of the trends. I hope you will take your time with our 2017 report, and allow your mind to wander productively. If you use our trends during an annual meeting to set your strategy for the coming year, that’s a good start—but it isn’t enough to safeguard your organization from what’s on the horizon. Organizations that use a formal process to research and track trends are more likely to reduce risk, harness new opportunities and drive change within their fields. What comes next won’t arrive fully formed. The future is yours to build. The Future Today Institute is eager to help you in 2017 and beyond. This is a robust, detailed document– don’t try to read it in one sitting. Start with the executive summary, and read through the top trends listed for your industry. In the coming weeks, spend some time with all of the trends. I hope you will take your time with our 2017 report, and allow your mind to wander productively. Amy Webb | Founder | Future Today Institute 2 © 2017 Future Today Institute

3. Key Takeaways • Convergence: In 2017, a critical mass of emerging technologies will start to converge, finding advanced uses beyond initial testing and applied research. That’s a signal worth paying attention to. We have devoted extra attention to artificial intelligence, mixed reality, object recognition systems, robots, autonomous vehicles, genomics, bioelectronics and automation. • Artificial Intelligence: For the first time, artificial intelligence research has advanced enough that it is now a core component of most of our trends. It is vitally important that all decision-makers within an organization familiarize themselves with what AI is, what it is not, and why it matters. We have included an AI Primer in our Trend Re- port this year to aid in that effort. • Crossover Trends: Leaders must pay attention to signals outside their immediate industries. In 2017 and beyond, technology developments in one industry sector will impact many others. For example, why should a logistics company like UPS or a grocery store chain like Kroger pay close attention to gene editing? Well...advancements in the CRISPR gene editing technique will lead to seeds for hyper-productive plants that require just a few feet of space and don’t need much water. Those plants could be farmed within dense urban areas, decreasing a reliance on local grocery stores. This would impact merchants, importers, truck drivers, UPC code sticker pro- viders, and marketing agencies, which would all experience a loss in profit. It would devastate the farmers in countries such as Brazil, Thailand and Mexico, who could rise up or revolt, causing political instability in those countries. This scenario isn’t guaranteed, but it is plausible, and it’s why UPS and Kroger should at least have gene editing on their 2017 radar. We can very easily build scenarios connecting the dots between myriad technologies, companies and industry sectors. For that reason, we encourage you to pay close attention to technology trends adjacent to your industry. EXECUTIVE SUMMARY Our mission at the Future Today Institute is to help organizations see around corners. Leaders tend to make bad decisions under duress. When surprised by a new, disruptive technology, their “flight-or-fight” response system kicks in, and they either ignore important tech trends and imperil their companies, or they act rashly and make ill-informed investments. Right now, all organizations, regardless of their size and scope, should be paying close attention to the fringe so that when a new technology arises, teams can evaluate their options rationally. © 2017 Future Today Institute3

4. • New Ecosystems: Many of the areas we’ve included in this report during the past decade have moved from the fringe towards the mainstream. In the process entire new ecosystems have blossomed: autonomous vehicles, genetics, robotics and the like. We have grouped these together in this year’s report to help you gain a deeper understanding of their ecosystems. • R&D Moves From Universities To Corporations: One observation we made while preparing our 2017 report: some of the unusual suspects we tracked on the fringes turned out to be R&D departments within very large, established corporations. This is because companies are courting academia now more than ever, and in some cases poaching entire research teams. Companies are successfully mimicking a university culture within their walls, with one big exception: money. They’re able to provide signiﬁcantly more resources and exponentially higher salaries than what’s offered in academe. • Government Policy: Both in the U.S. and elsewhere in the world, policy, privacy and security will be more complicated than ever in the coming year. Technology is changing faster than the government’s ability to legislate and regulate it—this will lead to complicated discussions and debates in the year ahead. • More Trends Than Ever: Our biggest takeaway (perhaps yours too, if you took a peak at the very end of the report) is that there are many more tech trends to pay attention to in 2017 than in previous years. Technology begets technology. We are witnessing an explosion in slow motion. Real trends worth your time and attention don’t have clever names. They don’t sound “trendy.” EXECUTIVE SUMMARY © 2017 Future Today Institute4

5. Our Trend Report this year is intentionally dense—there’s a lot here to digest. That’s because it’s meant as a practical resource for you and your organization. We don’t want you to skim through this during your lunch break. Instead, use it to listen for the signals talking and to advise your strategic thinking throughout 2017. Don’t discount a trend simply because at ﬁrst glance it doesn’t seem to relate directly to you or your ﬁeld. Instead, think about these 159 trends and ask yourself the following questions: 01 How does this trend impact our industry and all of its parts? 02 Who are the drivers of change in this trend? Which companies, leaders, founders, startups, researchers? 03 How are companies/ agencies/ organizations in adjacent spaces addressing this trend? 04 Where does this trend create potential new partners or collaborators for us? 05 How are our competitors/ related agencies harnessing this trend (or failing to do so?) 06 Which of our customer segments—existing, former, potential, theoretical—does this trend address? 07 How will the wants, needs and expectations of our customers change as a result of this trend? 08 Will this trend create new competitors for us? 09 How does this trend inspire us? 10 How does this trend help us think about innovation? This is a big report. We don’t want you to skim through this during your lunch break. 10 QUESTIONS How to relate these trends back to your organization in 2017 5 © 2017 Future Today Institute

6. Advertising, Public Relations Key Trend Themes For 2017 Artificial Intelligence Recognition Digital Frailty Video Mixed Reality Security Privacy Big Data Drones Automation Internet Mobs and Trolls Wearables Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence (whole section) 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 17 Smart Virtual Personal Assistants 18 Ambient Interfaces 19 Deep Linking 20 Consolidation in AI 24 Robot Companions 26 Ethical Manufacturing 29 Productivity Bots 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 36 Ambient Proximity 37 Character Recognition and Analytics 38 Attention 39 Digital Frailty 41 Limited-Edition News Products 43 One-To-Few Publishing 47 Conversational Interfaces 48 Dynamic Listicles 50 Connected TVs 51 Cord Cutting 53 Streaming Social Video 54 Media Consolidation 56 Crowdlearning 57 Blocking the Ad Blockers 59 Leaking 60 The First Amendment in a Digital Age 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 71 Glitches 75 Prize Hacks 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 83 Trolls 84 Authenticity 91 Ownership 93 Organizational Doxing 98 VR Marketing 99 FOBO (Fear Of Being Offline) 100 Retail APIs 102 Sense and Avoid Technology 121 Internet Mob Justice 133 Head Mounted Displays 134 Smartwatches 137 Women/ Wearables THE MOST IMPORTANT TRENDS FOR YOUR INDUSTRY AND ORGANIZATION We’ve created lists to help you find the most important tech trends that will matter most to you, your organization and your industry in 2017. For your convenience, industries are listed alphabetically along with the corresponding trends. © 2017 Future Today Institute6

7. Pay Special Attention To These Trends In Our Report 01 Artiﬁcial Intelligence 02 Real-Time Machine Learning 13 Accountability and Trust 15 Deep Learning 16 Cognitive Computing 20 Consolidation in AI 22 Smart Dust 25 Collaborative Robots 26 Ethical Manufacturing 32 Sharing Economy and Lendership 35 Adversarial Images 61 Synthetic Data Sets 64 Augmented Reality 67 Data Retention Policies 69 Zero Day Exploits 71 Glitches 73 Open Source App Vulnerabilities 75 Prize Hacks 81 Differential Privacy 84 Authenticity 87 Eye in the Sky 88 Right to Eavesdrop/ Be Eavesdropped On 89 Drone Surveillance 103 Drone Lanes 106 Microdrones 107 Drone Delivery 108 Internet of Things 109 Intelligent Cameras 110 Open Source Systems 111 Adaptive Driving Systems 112 Vehicle-to-Vehicle Communications 115 Autonomous Vehicle Legislation 126 Molecular Programming 129 Synthetic Biology 131 Norms and Regulations (Biological) 148 Deep Learning For Food Recognition 149 Smart Farms 150 Terraforming 151 Cultivated Food and Beverage 152 Anthropocene and Climate Agriculture Key Trend Themes For 2017 Artiﬁcial Intelligence Robotics Recognition Augmented Reality Security Privacy Big Data Drones Internet of Things Automation Self-Driving Vehicles Genomic Editing Deep Learning Anthropocene and Climate © 2017 Future Today Institute7

8. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 13 Accountability and Trust 15 Deep Learning 16 Cognitive Computing 18 Ambient Interfaces 20 Consolidation in AI 21 Human-Machine Interfaces 24 Robot Companions 25 Collaborative Robots 31 Nanodegrees 32 Sharing Economy and Lendership 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 36 Ambient Proximity 56 Crowdlearning 61 Synthetic Data Sets 64 Augmented Reality 66 Holograms 67 Data Retention Policies 68 Remote Kill Switches 69 Zero Day Exploits 70 Backdoors 71 Glitches 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 81 Differential Privacy 86 Encryption Management 88 Right to Eavesdrop/ Be Eavesdropped On 89 Drone Surveillance 93 Organizational Doxing 99 FOBO (Fear Of Being Offline) 100 Retail APIs 103 Drone Lanes 104 Clandestine, Disappearing Drones 105 Autonomous Underwater Vehicles 106 Microdrones 107 Drone Delivery 108 Internet of Things 109 Intelligent Cameras 110 Open Source Systems 111 Adaptive Driving Systems 112 Vehicle-to-Vehicle Communications 113 Autonomous Testing Facilities 114 Solar Highways 115 Autonomous Vehicle Legislation 123 City-Level Cyber Security 124 Smart City Systems 132 Biointerfaces 133 Head Mounted Displays 134 Smartwatches 136 Connected Fabrics 143 Thinkables 152 Anthropocene and Climate 153 Space Exploration 154 Invisibility Cloaks 157 Internet of X 158 5G Infrastructure Key Trend Themes For 2017 Artificial Intelligence Robotics Human-Machine Interfaces Recognition Mixed Reality Security Privacy Big Data Drones Internet of Things Automation Self-Driving Vehicles Smart Cities Wearables © 2017 Future Today Institute8

9. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 16 Cognitive Computing 17 Smart Virtual Personal Assistants 20 Consolidation in AI 26 Ethical Manufacturing 27 Universal Basic Income 28 Artificial Intelligence in Hiring 29 Productivity Bots 31 Nanodegrees 33 Faceless Recognition 34 Bias in Recognition Algorithms 36 Ambient Proximity 37 Character Recognition and Analytics 39 Digital Frailty 54 Media Consolidation 57 Blocking the Ad Blockers 63 Virtual Reality 64 Augmented Reality 67 Data Retention Policies 68 Remote Kill Switches 70 Backdoors 71 Glitches 72 Darknets 75 Prize Hacks 86 Encryption Management 88 Right to Eavesdrop/ Be Eavesdropped On 90 Private Networks 91 Ownership 93 Organizational Doxing 95 E-Residents 96 Social Payments 97 Bitcoin and Blockchain 99 FOBO (Fear Of Being Offline) 100 Retail APIs 101 Digital Associates 118 Old Laws Clash With New Technology 121 Internet Mob Justice 156 3D Printing 157 Internet of X 158 5G Business Associations Key Trend Themes For 2017 Artificial Intelligence Recognition Digital Frailty Security Privacy Big Data E-Residents Social Payments Bitcoin and Blockchain Automation Internet Mobs and Trolls © 2017 Future Today Institute9

10. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence (whole section) 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 16 Cognitive Computing 18 Ambient Interfaces 20 Consolidation in AI 21 Human-Machine Interfaces 27 Universal Basic Income 30 Adaptive Learning 31 Nanodegrees 33 Faceless Recognition 34 Bias in Recognition Algorithms 36 Ambient Proximity 37 Character Recognition and Analytics 38 Attention 39 Digital Frailty 47 Conversational Interfaces 48 Dynamic Listicles 59 Leaking 60 The First Amendment in a Digital Age 61 Synthetic Data Sets 62 Torrents 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 68 Zero Day Exploits 69 Backdoors 71 Glitches 72 Darknets 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 79 Weaponizing Wikileaks 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 85 Revenge Porn 86 Encryption Management 88 Right to Eavesdrop/ Be Eavesdropped On 91 Ownership 92 Uploading Photos To Law Enforcement Databases 93 Organizational Doxing 99 FOBO (Fear Of Being Offline) 108 Internet of Things 157 Internet of X 158 5G Colleges, Universities & Schools Key Trend Themes For 2017 Artificial Intelligence Robotics Human-Machine Interfaces Recognition Digital Frailty Mixed Reality Security Privacy Big Data Internet of Things Automation © 2017 Future Today Institute10

11. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 13 Accountability and Trust 14 Bots 32 Sharing Economy and Lendership 34 Bias in Recognition Algorithms 36 Ambient Proximity 37 Character Recognition and Analytics 61 Synthetic Data Sets 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 75 Prize Hacks 83 Trolls 93 Organizational Doxing 96 Social Payments 99 FOBO (Fear Of Being Offline) 100 Retail APIs 101 Digital Associates 107 Drone Delivery 108 Internet of Things 133 Head Mounted Displays 134 Smartwatches 136 Connected Fabrics 137 Women/ Wearables 138 Kids/ Wearables 139 Pets/ Wearables 142 Earables 143 Thinkables 148 Deep Learning For Food Recognition 151 Cultivated Food and Beverage 156 3D Printing 157 Internet of X 158 5G Consumer Package Goods & Retail Key Trend Themes For 2017 Artificial Intelligence Mixed Reality Security Privacy Big Data Social Payments Drones Internet of Things Wearables © 2017 Future Today Institute11

12. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 12 Hidden Bias in AI 13 Accountability and Trust 20 Consolidation in AI 26 Ethical Manufacturing 28 Artificial Intelligence in Hiring 31 Nanodegrees 54 Media Consolidation 59 Leaking 60 The First Amendment in a Digital Age 67 Data Retention Policies 69 Zero Day Exploits 70 Backdoors 71 Glitches 75 Prize Hacks 76 Automated Hacking 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 86 Encryption Management 88 Right to Eavesdrop/ Be Eavesdropped On 91 Ownership 93 Organizational Doxing 97 Bitcoin and Blockchain 118 Old Laws Clash With New Technology 121 Internet Mob Justice Corporate Boards Key Trend Themes For 2017 Artificial Intelligence Robotics Human-Machine Interfaces Security Privacy Big Data E-Residents Bitcoin and Blockchain Automation Internet Mobs and Trolls © 2017 Future Today Institute12

13. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence (whole section) 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 20 Consolidation in AI 21 Human-Machine Interfaces 22 Smart Dust 23 Soft Robotics 25 Collaborative Robots 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 36 Ambient Proximity 37 Character Recognition and Analytics 52 WebRTC 56 Crowdlearning 61 Synthetic Data Sets 62 Torrents 63 Virtual Reality 64 Augmented Reality 66 Holograms 67 Data Retention Policies 68 Remote Kill Switches 69 Zero Day Exploits 70 Backdoors 71 Glitches 72 Darknets 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 77 Offensive Government Hacking 78 Cyber Mission Forces in the Field 79 Weaponizing Wikileaks 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 86 Encryption Management 87 Eye in the Sky 88 Right to Eavesdrop/ Be Eavesdropped On 89 Drone Surveillance 90 Private Networks 92 Uploading Photos To Law Enforcement Databases 93 Organizational Doxing 99 Bitcoin and Blockchain 103 Drone Lanes 104 Clandestine, Disappearing Drones 105 Autonomous Underwater Vehicles 106 Microdrones 107 Drone Delivery 108 Internet of Things 109 Intelligent Cameras 110 Open Source Systems 111 Adaptive Driving Systems 112 Vehicle-to-Vehicle Communications 113 Autonomous Testing Facilities 114 Solar Highways 115 Autonomous Vehicle Legislation 119 Digital Caliphate 120 Asking Tech Companies To Help Fight Terrorism 121 Internet Mob Justice 125 Precision Medicine 126 Molecular Programming 128 Neuroenhancers 129 Synthetic Biology 131 Norms and Regulations (Biological) 132 Biointerfaces 133 Head Mounted Displays 134 Smartwatches 135 Wireless Body Area Networks 136 Connected Fabrics 140 Tattooables 141 Ingestibles/ Implantables 142 Earables 143 Thinkables 144 Smart Thread 145 Bioelectronics 147 Touch-Sensitive Prosthetics 154 Invisibility Cloaks 155 Quantum Computers 156 3D Printing 157 Internet of X 158 5G Defense Key Trend Themes For 2017 Artificial Intelligence Robotics Human-Machine Interfaces Recognition Mixed Reality Security Privacy Big Data Bitcoin and Blockchain Drones Internet of Things Automation Self-Driving Vehicles Internet Mobs and Trolls Genomic Editing Wearables © 2017 Future Today Institute13

14. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence (whole section) 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 18 Ambient Interfaces 20 Consolidation in AI 21 Human-Machine Interfaces 24 Robot Companions 56 Crowdlearning 61 Synthetic Data Sets 63 Virtual Reality 67 Data Retention Policies 93 Organizational Doxing 99 FOBO (Fear Of Being Offline) 108 Internet of Things 125 Precision Medicine 126 Molecular Programming 127 Nanobot Treatments 128 Neuroenhancers 129 Synthetic Biology 130 Running Out of Space For Genome Storage 131 Norms and Regulations (Biological) 132 Biointerfaces 133 Head Mounted Displays 134 Smartwatches 135 Wireless Body Area Networks 140 Tattooables 141 Ingestibles/ Implantables 142 Earables 143 Thinkables 144 Smart Thread 145 Bioelectronics 146 Patient-Generated Health Data 147 Touch-Sensitive Prosthetics 156 3D Printing 157 Internet of X 158 5G Doctors & Other Health Professionals Key Trend Themes For 2017 Artificial Intelligence Human-Machine Interfaces Recognition Mixed Reality Security Privacy Big Data Internet of Things Genomic Editing Wearables © 2017 Future Today Institute14

15. Pay Special Attention To These Trends In Our Report 01 Artiﬁcial Intelligence 02 Real-Time Machine Learning 13 Accountability and Trust 15 Deep Learning 16 Cognitive Computing 20 Consolidation in AI 21 Human-Machine Interfaces 22 Smart Dust 23 Soft Robotics 56 Crowdlearning 61 Synthetic Data Sets 67 Data Retention Policies 93 Organizational Doxing 108 Internet of Things 125 Precision Medicine 126 Molecular Programming 127 Nanobot Treatments 128 Neuroenhancers 129 Synthetic Biology 130 Running Out of Space For Genome Storage 131 Norms and Regulations (Biological) 132 Biointerfaces 134 Smartwatches 135 Wireless Body Area Networks 140 Tattooables 141 Ingestibles/ Implantables 142 Earables 143 Thinkables 144 Smart Thread 145 Bioelectronics 146 Patient-Generated Health Data 147 Touch-Sensitive Prosthetics 156 3D Printing 157 Internet of X 158 5G Drug Manufacturers/ Pharmaceuticals Key Trend Themes For 2017 Artiﬁcial Intelligence Robotics Human-Machine Interfaces Recognition Security Privacy Big Data Internet of Things Automation Genomic Editing Wearables Bioelectronics © 2017 Future Today Institute15

16. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 03 Image Completion 05 Natural Language Generation 08 Zero Knowledge Proofs 10 Algorithm Marketplaces 11 Pre-Trained AI Chips 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 17 Smart Virtual Personal Assistants 18 Ambient Interfaces 19 Deep Linking 20 Consolidation in AI 31 Nanodegrees 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 37 Character Recognition and Analytics 56 Crowdlearning 61 Synthetic Data Sets 67 Data Retention Policies 69 Zero Day Exploits 70 Backdoors 71 Glitches 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 81 Differential Privacy 86 Encryption Management 93 Organizational Doxing 95 E-Residents 96 Social Payments 97 Bitcoin and Blockchain 118 Old Laws Clash With New Technology 121 Internet Mob Justice Finance Key Trend Themes For 2017 Artificial Intelligence Recognition Bots Security Privacy Big Data E-Residents Social Payments Bitcoin and Blockchain Automation Internet Mobs and Trolls © 2017 Future Today Institute16

17. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 16 Cognitive Computing 20 Consolidation in AI 24 Robot Companions 26 Ethical Manufacturing 27 Universal Basic Income 30 Adaptive Learning 31 Nanodegrees 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 37 Character Recognition and Analytics 39 Digital Frailty 40 Nutritional Labels For News 41 Limited-Edition News Products 43 One-To-Few Publishing 44 Journalism as a Service (Jaas) 47 Conversational Interfaces 54 Media Consolidation 56 Crowdlearning 59 Leaking 60 The First Amendment in a Digital Age 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 79 Weaponizing Wikileaks 93 Organizational Doxing 95 E-Residents 96 Social Payments 97 Bitcoin and Blockchain 121 Internet Mob Justice 123 City-Level Cyber Security 124 Smart City Systems 152 Anthropocene and Climate Foundations, Philanthropists & Non-profits Key Trend Themes For 2017 Artificial Intelligence Robotics Recognition Digital Frailty Mixed Reality Security Privacy Big Data Bitcoin and Blockchain Automation Internet Mobs and Trolls Smart Cities Anthropocene and Climate © 2017 Future Today Institute17

18. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence (whole section) 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 17 Smart Virtual Personal Assistants 18 Ambient Interfaces 19 Deep Linking 20 Consolidation in AI 21 Human-Machine Interfaces 22 Smart Dust 24 Robot Companions 26 Ethical Manufacturing 27 Universal Basic Income 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 36 Ambient Proximity 37 Character Recognition and Analytics 39 Digital Frailty 40 Nutritional Labels For News 43 One-To-Few Publishing 47 Conversational Interfaces 49 Real-Time Fact Checking 52 WebRTC 54 Media Consolidation 56 Crowdlearning 57 Blocking the Ad Blockers 58 Natural Language Generation for Reading Levels 59 Leaking 60 The First Amendment in a Digital Age 61 Synthetic Data Sets 62 Torrents 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 68 Remote Kill Switches 69 Zero Day Exploits 70 Backdoors 71 Glitches 72 Darknets 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 77 Offensive Government Hacking 78 Cyber Mission Forces in the Field 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 85 Revenge Porn 86 Encryption Management 87 Eye in the Sky 88 Right to Eavesdrop/ Be Eavesdropped On 89 Drone Surveillance 90 Private Networks 91 Ownership 92 Uploading Photos To Law Enforcement Databases 93 Organizational Doxing 95 E-Residents 97 Bitcoin and Blockchain 103 Drone Lanes 104 Clandestine, Disappearing Drones 105 Autonomous Underwater Vehicles 106 Microdrones 107 Drone Delivery 108 Internet of Things 110 Open Source Systems 111 Adaptive Driving Systems 112 Vehicle-to-Vehicle Communications 113 Autonomous Testing Facilities 114 Solar Highways 115 Autonomous Vehicle Legislation 118 Old Laws Clash With New Technology 119 Digital Caliphate 120 Asking Tech Companies To Help Fight Terrorism 121 Internet Mob Justice 122 Overhauling Government Tech Infrastructure 123 City-Level Cyber Security 124 Smart City Systems 130 Running Out of Space For Genome Storage 131 Norms and Regulations (Biological) 146 Patient-Generated Health Data 152 Anthropocene and Climate 155 Quantum Computers 157 Internet of X 158 5G Human Resources Government, Politics, Legal, Policy Key Trend Themes For 2017 Artificial Intelligence Robotics Human-Machine Interfaces Recognition Digital Frailty Mixed Reality Security Privacy Big Data Bitcoin and Blockchain Drones Internet of Things Automation Self-Driving Vehicles Internet Mobs and Trolls Genomic Editing © 2017 Future Today Institute18

19. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 03 Image Completion 04 Predictive Machine Vision 05 Natural Language Generation 08 Zero Knowledge Proofs 09 Algorithmic Personality Detection 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 19 Deep Linking 20 Consolidation in AI 24 Robot Companions 25 Collaborative Robots 28 Artificial Intelligence in Hiring 29 Productivity Bots 30 Adaptive Learning 31 Nanodegrees 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 37 Character Recognition and Analytics 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 70 Backdoors 75 Prize Hacks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 86 Encryption Management 93 Organizational Doxing 99 FOBO (Fear Of Being Offline) 118 Old Laws Clash With New Technology 128 Neuroenhancers © 2017 Future Today Institute Key Trend Themes For 2017 Artificial Intelligence Robotics Recognition Mixed Reality Security Privacy Big Data Automation Mixed Reality Security Privacy Big Data Automation 19

20. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence (whole section) 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 18 Ambient Interfaces 20 Consolidation in AI 21 Human-Machine Interfaces 22 Smart Dust 24 Robot Companions 25 Collaborative Robots 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 36 Ambient Proximity 37 Character Recognition and Analytics 56 Crowdlearning 62 Torrents 63 Virtual Reality 64 Augmented Reality 67 Data Retention Policies 68 Remote Kill Switches 69 Zero Day Exploits 70 Backdoors 71 Glitches 72 Darknets 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 77 Offensive Government Hacking 78 Cyber Mission Forces in the Field 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 85 Revenge Porn 86 Encryption Management 87 Eye in the Sky 88 Right to Eavesdrop/ Be Eavesdropped On 89 Drone Surveillance 90 Private Networks 91 Ownership 92 Uploading Photos To Law Enforcement Databases 93 Organizational Doxing 96 Social Payments 97 Bitcoin and Blockchain 103 Drone Lanes 104 Clandestine, Disappearing Drones 105 Autonomous Underwater Vehicles 106 Microdrones 107 Drone Delivery 108 Internet of Things 109 Intelligent Cameras 110 Open Source Systems 111 Adaptive Driving Systems 112 Vehicle-to-Vehicle Communications 113 Autonomous Testing Facilities 114 Solar Highways 115 Autonomous Vehicle Legislation 118 Old Laws Clash With New Technology 120 Asking Tech Companies To Help Fight Terrorism 121 Internet Mob Justice 123 City-Level Cyber Security 124 Smart City Systems 132 Biointerfaces 154 Invisibility Cloaks 155 Quantum Computers 157 Internet of X 158 5G Law Enforcement Key Trend Themes For 2017 Artificial Intelligence Robotics Human-Machine Interfaces Recognition Mixed Reality Security Privacy Big Data Social Payments Bitcoin and Blockchain Drones Internet of Things Automation Self-Driving Vehicles Internet Mobs and Trolls Smart Cities © 2017 Future Today Institute20

21. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 03 Image Completion 04 Predictive Machine Vision 05 Natural Language Generation 08 Zero Knowledge Proofs 09 Algorithmic Personality Detection 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 16 Cognitive Computing 18 Ambient Interfaces 20 Consolidation in AI 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 37 Character Recognition and Analytics 49 Real-Time Fact Checking 62 Torrents 63 Virtual Reality 64 Augmented Reality 67 Data Retention Policies 68 Remote Kill Switches 69 Zero Day Exploits 70 Backdoors 71 Glitches 72 Darknets 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 77 Offensive Government Hacking 78 Cyber Mission Forces in the Field 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 85 Revenge Porn 86 Encryption Management 87 Eye in the Sky 88 Right to Eavesdrop/ Be Eavesdropped On 89 Drone Surveillance 90 Private Networks 91 Ownership 92 Uploading Photos To Law Enforcement Databases 93 Organizational Doxing 95 E-Residents 96 Social Payments 97 Bitcoin and Blockchain 103 Drone Lanes 104 Clandestine, Disappearing Drones 105 Autonomous Underwater Vehicles 106 Microdrones 107 Drone Delivery 108 Internet of Things 110 Open Source Systems 112 Vehicle-to-Vehicle Communications 115 Autonomous Vehicle Legislation 118 Old Laws Clash With New Technology 120 Asking Tech Companies To Help Fight Terrorism 121 Internet Mob Justice Lawyers, Law Firms & Lobbyists Key Trend Themes For 2017 Artificial Intelligence Recognition Mixed Reality Security Privacy Big Data E-Residents Drones Internet of Things Automation Self-Driving Vehicles Internet Mobs and Trolls © 2017 Future Today Institute21

22. Pay Special Attention To These Trends In Our Report 01 Artiﬁcial Intelligence 02 Real-Time Machine Learning 04 Predictive Machine Vision 03 Image Completion 12 Hidden Bias in AI 13 Accountability and Trust 15 Deep Learning 16 Cognitive Computing 20 Consolidation in AI 21 Human-Machine Interfaces 22 Smart Dust 23 Soft Robotics 24 Robot Companions 25 Collaborative Robots 56 Crowdlearning 61 Synthetic Data Sets 63 Virtual Reality 64 Augmented Reality 93 Organizational Doxing 108 Internet of Things 125 Precision Medicine 126 Molecular Programming 127 Nanobot Treatments 128 Neuroenhancers 129 Synthetic Biology 130 Running Out of Space For Genome Storage 131 Norms and Regulations (Biological) 132 Biointerfaces 134 Smartwatches 135 Wireless Body Area Networks 136 Connected Fabrics 140 Tattooables 141 Ingestibles/ Implantables 142 Earables 143 Thinkables 144 Smart Thread 145 Bioelectronics 146 Patient-Generated Health Data 147 Touch-Sensitive Prosthetics 156 3D Printing 157 Internet of X 158 5G Medical, Health, Life Sciences Key Trend Themes For 2017 Artiﬁcial Intelligence Robotics Human-Machine Interfaces Recognition Mixed Reality Security Privacy Big Data Internet of Things Genomic Editing Wearables Bioelectronics © 2017 Future Today Institute22

23. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 03 Image Completion 04 Predictive Machine Vision 05 Natural Language Generation 06 Generative Algorithms For Voice 07 Generative Algorithms For Sound 09 Algorithmic Personality Detection 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 17 Smart Virtual Personal Assistants 18 Ambient Interfaces 19 Deep Linking 20 Consolidation in AI 22 Smart Dust 29 Productivity Bots 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 37 Character Recognition and Analytics 38 Attention 39 Digital Frailty 40 Nutritional Labels For News 41 Limited-Edition News Products 42 Artificial Intelligence For News 43 One-To-Few Publishing 44 Journalism as a Service (Jaas) 45 Transparency in Metrics 46 Intentional Rabbit Holes 47 Conversational Interfaces 48 Dynamic Listicles 49 Real-Time Fact Checking 50 Connected TVs 51 Cord Cutting 52 WebRTC 53 Streaming Social Video 54 Media Consolidation 55 CARv2.0 56 Crowdlearning 57 Blocking the Ad Blockers 58 Natural Language Generation for Reading Levels 59 Leaking 60 The First Amendment in a Digital Age 61 Synthetic Data Sets 62 Torrents 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 69 Zero Day Exploits 71 Glitches 73 Open Source App Vulnerabilities 75 Prize Hacks 76 Automated Hacking 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 86 Encryption Management 91 Ownership 93 Organizational Doxing 96 Social Payments 103 Drone Lanes 118 Old Laws Clash With New Technology 121 Internet Mob Justice 157 Internet of X 158 5G News, Journalism, Media, Publishing Key Trend Themes For 2017 Artificial Intelligence Recognition Digital Frailty Accountability Video Mixed Reality Security Privacy Big Data Social Payments Drones Automation Internet Mobs and Trolls © 2017 Future Today Institute23

24. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 09 Algorithmic Personality Detection 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 17 Smart Virtual Personal Assistants 28 Artificial Intelligence in Hiring 29 Productivity Bots 30 Adaptive Learning 31 Nanodegrees 32 Sharing Economy and Lendership 34 Bias in Recognition Algorithms 37 Character Recognition and Analytics 58 Natural Language Generation for Reading Levels 67 Data Retention Policies 75 Prize Hacks 83 Trolls 84 Authenticity 86 Encryption Management 91 Ownership 93 Organizational Doxing 157 Internet of X 158 5G Professional Services Key Trend Themes For 2017 Artificial Intelligence Robotics Recognition Mixed Reality Security Privacy Big Data Automation © 2017 Future Today Institute24

25. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence (whole section) 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 18 Ambient Interfaces 19 Deep Linking 20 Consolidation in AI 21 Human-Machine Interfaces 25 Collaborative Robots 26 Ethical Manufacturing 29 Productivity Bots 31 Nanodegrees 33 Faceless Recognition 34 Bias in Recognition Algorithms 35 Adversarial Images 36 Ambient Proximity 51 Cord Cutting 52 WebRTC 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 68 Remote Kill Switches 69 Zero Day Exploits 70 Backdoors 71 Glitches 72 Darknets 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 76 Automated Hacking 77 Offensive Government Hacking 78 Cyber Mission Forces in the Field 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 85 Revenge Porn 86 Encryption Management 87 Eye in the Sky 88 Right to Eavesdrop/ Be Eavesdropped On 89 Drone Surveillance 90 Private Networks 91 Ownership 92 Uploading Photos To Law Enforcement Databases 93 Organizational Doxing 95 E-Residents 96 Social Payments 97 Bitcoin and Blockchain 103 Drone Lanes 104 Clandestine, Disappearing Drones 105 Autonomous Underwater Vehicles 106 Microdrones 107 Drone Delivery 108 Internet of Things 120 Asking Tech Companies To Help Fight Terrorism 121 Internet Mob Justice 124 Smart City Systems 153 Space Exploration 155 Quantum Computers 156 3D Printing 157 Internet of X 158 5G Technology Companies/ Manufacturers Key Trend Themes For 2017 Artificial Intelligence Robotics Human-Machine Interfaces Recognition Mixed Reality Security Privacy Big Data E-Residents Drones Internet of Things Automation Internet Mobs and Trolls Smart Cities Space Exploration © 2017 Future Today Institute25

26. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 09 Algorithmic Personality Detection 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 20 Consolidation in AI 25 Collaborative Robots 26 Ethical Manufacturing 27 Universal Basic Income 28 Artificial Intelligence in Hiring 29 Productivity Bots 31 Nanodegrees 32 Sharing Economy and Lendership 34 Bias in Recognition Algorithms 36 Ambient Proximity 37 Character Recognition and Analytics 39 Digital Frailty 43 One-To-Few Publishing 54 Media Consolidation 56 Crowdlearning 63 Virtual Reality 64 Augmented Reality 67 Data Retention Policies 73 Open Source App Vulnerabilities 75 Prize Hacks 79 Weaponizing Wikileaks 80 Anonymity 81 Differential Privacy 82 Digital Self-Incrimination 83 Trolls 84 Authenticity 86 Encryption Management 92 Uploading Photos To Law Enforcement Databases 93 Organizational Doxing 95 E-Residents 118 Old Laws Clash With New Technology 152 Anthropocene and Climate 157 Internet of X 158 5G Trade, Professional Associations, Interest Groups Key Trend Themes For 2017 Artificial Intelligence Recognition Digital Frailty Mixed Reality Security Privacy Big Data E-Residents Automation Anthropocene and Climate © 2017 Future Today Institute26

27. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 09 Algorithmic Personality Detection 12 Hidden Bias in AI 13 Accountability and Trust 15 Deep Learning 16 Cognitive Computing 17 Smart Virtual Personal Assistants 20 Consolidation in AI 24 Robot Companions 32 Sharing Economy and Lendership 43 One-To-Few Publishing 53 Streaming Social Video 63 Virtual Reality 64 Augmented Reality 65 360-degree Video 66 Holograms 67 Data Retention Policies 73 Open Source App Vulnerabilities 74 Selfie Security 75 Prize Hacks 83 Trolls 84 Authenticity 86 Encryption Management 93 Organizational Doxing 103 Drone Lanes 107 Drone Delivery 152 Anthropocene and Climate 153 Space Exploration 158 5G Travel, Entertainment Key Trend Themes For 2017 Artificial Intelligence Robotics Recognition Mixed Reality Security Privacy Big Data Drones Automation Anthropocene and Climate Space Exploration © 2017 Future Today Institute27

28. Pay Special Attention To These Trends In Our Report 01 Artificial Intelligence 02 Real-Time Machine Learning 03 Image Completion 04 Predictive Machine Vision 05 Natural Language Generation 08 Zero Knowledge Proofs 09 Algorithmic Personality Detection 12 Hidden Bias in AI 13 Accountability and Trust 14 Bots 15 Deep Learning 16 Cognitive Computing 19 Deep Linking 20 Consolidation in AI 24 Robot Companions 25 Collaborative Robots 26 Ethical Manufacturing 27 Universal Basic Income 28 Artificial Intelligence in Hiring 29 Productivity Bots 30 Adaptive Learning 31 Nanodegrees 33 Faceless Recognition 34 Bias in Recognition Algorithms 37 Character Recognition and Analytics 63 Virtual Reality 64 Augmented Reality 66 Holograms 67 Data Retention Policies 72 Darknets 73 Open Source App Vulnerabilities 81 Differential Privacy 86 Encryption Management 93 Organizational Doxing 95 E-Residents 110 Open Source Systems 112 Vehicle-to-Vehicle Communications 115 Autonomous Vehicle Legislation 158 5G Work (Future of) Key Trend Themes For 2017 Artificial Intelligence Robotics Recognition Mixed Reality Security Privacy Big Data E-Residents Automation Self-Driving Vehicles © 2017 Future Today Institute28

29. The Future Today Institute’s forecasting model relies on quantitative and qualitative data. Our six steps alternate between broad and narrow scopes, which include: identifying very early stage fringe research, focusing on patterns, interrogating trend candidates, calculating a trend’s trajectory, writing scenarios and ﬁnally pressure-testing strategies and recommendations. METHODOLOGY 29 © 2017 Future Today Institute

30. HOW TO USE THE 2017 REPORT Our 2017 Trend Report reveals strategic opportunities and challenges for your organization in the coming year. The Future Today Institute’s annual Trend Report prepares leaders and organizations for the year ahead, so that you are better positioned to see emerging technology and adjust your strategy accordingly. Use our report to identify near-future business disruption and competitive threats while simultaneously ﬁnding new collaborators and partners. Most importantly, use our report as a jumping off point for deeper strategic planning. Explaining why these trends matter. Rather than simply offering an overview of the trends that will matter in 2017, our annual report takes the additional step of explaining why and how these trends will impact your organization. In some cases, you will see very speciﬁc use cases and descriptive illustrations, so that you can more clearly envision the potential outcomes of these trends during the next 12 months. © 2017 Future Today Institute30

31. You’ll ﬁnd six important pieces of information with each trend in this report. 01 Key Insight Short, easy explanation of this trend so that you can internalize it and discuss with your colleagues. 02 Examples Real-world use cases, some of which will sound familiar. 03 What’s Next What this trend means for you and your organization in the coming year. 04 Watchlist Notable companies, founders and researchers working in this trend space. 05 Years On The List We’ve noted how many years we’ve been tracking the trend, even as it has evolved. This is an indication of how the trend is progressing. 06 Action Meter An easy-to-read graphic indicating where the trend is along it’s trajectory. It tells you whether the trend needs monitoring, should inform your strategy, or requires action. We recommend using our 2017 Tech Trends Report as part of a formalized process to evaluate disruptive technologies throughout the year. © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action 31 01 05 02 03 06 04 HOW TO USE OUR REPORT

32. WHAT IS A TREND, EXACTLY? Mapping the future for your organization begins with identifying early signposts as you look out on the horizon. In order to chart the best way forward, you must understand emerging trends: what they are, what they aren’t, and how they operate. At any moment, there are hundreds of small shifts in technology—developments on the fringes of science and society—that will impact our lives in the future. A trend is a new manifestation of sustained change within an industry sector, society, or human behavior. A trend is more than the latest shiny object. Fundamentally, a trend leverages our basic human needs and desires in a meaningful way, and it aligns human nature with breakthrough technologies and inventions. All trends share a set of conspicuous, universal features: • A trend is driven by a basic human need, one that is catalyzed by new technology. • A trend is timely, but it persists. • A trend evolves as it emerges. • A trend can materialize as a series of unconnectable dots which begin out on the fringe and move to the mainstream. Identifying something as a trend means connecting the dots, or relating changes in the present to what’s coming in the future. To map what the future holds, seek out the early adopters, the hackers, the developers with seemingly impossible ideas. It’s within these circles that meaningful changes begin. As the trend evolves, the work of these disparate groups begins to overlap, until it converges in a single point—before perhaps evolving once again. © 2017 Future Today Institute32

33. WHAT IS A TREND, EXACTLY? Because trends are a different way of seeing and interpreting our current reality, they provide a useful framework to organize our thinking, especially when we’re hunting for the unknown and trying to learn something about which we do not yet know how to ask. There are ten modern sources of change in society with technology as the primary connector. Therefore, if we want to forecast the future of anything, we would need to plot out the intersecting vectors of change—their direction and magnitude—as they relate to new developments in emerging technology. These features are what make up a trend. Together they distinguish a trend from a fad, which will invariably pass. Trends are what help us to forecast the future. Wealth distribution Education Government Politics Public health Demography Economy Environment Journalism Media (our individual and collective use of social networks, chat services, digital video channels, photo sharing services and so on) 01 06 02 07 03 08 04 09 05 10 33 © 2017 Future Today Institute

34. WHAT IS A TREND, EXACTLY? The future is simultaneously 250 years, 3 decades, 1 months, 88 hours, 37 minutes and 14 seconds from right now. Forecast- ing the future requires thinking in contradictory ways. We must accept that the future is not predetermined—that we can both know what’s past the horizon and intervene to shape it—while simultaneously acknowledging that any number of variables, at any time, can inﬂuence an outcome. We must solve the paradox of the present by practicing ambidextrous thinking. When it comes to technology, it is helpful to organize the evolution of trends along six general time zones. They are not arbitrary; they follow the pattern of acceleration across various sectors of the tech ecosystem. For example, consider the evolution of cars: Futures of Cars, 2017 - 2057 Now: within the next 12 months. By the end of 2018, cars will be equipped with software updates and new sensors that perform more functions for the driver, such as parking and adaptive cruise control. Near-term: 1 - 5 years. By 2022, most cars will be equipped with cross-path cameras to sense nearby objects and they will have adaptive cruise control for driving in stop-and-go trafﬁc. They will offer many driverless functions—but you will still need to operate the car in neighbor- hoods and many city streets. Mid-range: 5 - 10 years. By 2027, advanced Lidar and WiFi technology will transmit your vehicle’s location and will recognize other vehicles sharing the road. This will begin to enable cars to drive themselves on highways and many city streets. Long-range: 10 - 20 years. By 2037, the highway system will have been upgraded to work in symbiosis with semi-autonomous vehicles. Human drivers will take over on smaller streets. On man- dated autonomous highway lanes, people will be free to read, watch videos or con- duct work. Far-range: 20 - 30 years. By 2047, we may no longer own cars and cities might no longer operate buses. In- stead, automated buses could be subsidized thought taxes and offered at no cost. Those with the means to do so may subscribe to a transportation service, which op- erates vehicles that are fully automated and will take them to destinations as desired. Distant: more than 30 years. By 2057, autonomous vehicles could be connected to a series of high-speed maglev trains, which may have started to supplant commercial air routes on the East and West coasts. © 2017 Future Today Institute The future is simultaneously 250 years, 3 decades, 1 months, 88 hours, 37 minutes and 14 seconds from right now. 34

35. Artificial Intelligence Second year on the list Key Insight Many facets of artificial intelligence (AI) have made our list since we first started publishing this report a decade ago. For 2017, we have grouped them all under one trend. What You Need To Know About AI Think about AI as the next layer of technology that will be integrated into everything you do professionally. Simply put, AI is a branch of computer science in which computers are programmed to do things that normally require human intelligence. This includes learning, reasoning, problem-solving, understanding language and perceiving a situation or environment. AI is an extremely large, broad field, which uses its own computer languages and even special kids of computer networks WHICH are modeled on our human brains. The idea that we might someday create artificially intelligent, sentient robots was first sug- gested by prominent philosophers in the mid-1600s. There are two kinds of AI: weak (or “narrow”) and strong (or “general”). When Netflix makes recommendations to you, or Amazon displays books you might like to read, that’s narrow AI. The H.A.L. supercomputer from 2001: A Space Odyssey, which was not only sentient, but decided it no longer had use for us humans, is a representation of artificial general intelligence. For the past six decades, researchers have been modeling AI using our own human brain as inspiration. Neural networks are the basic computer architecture that attempts to mimic some of what we know about how the human brain and central nervous system transfers signals. A neural network is the place where information is sent and received, and a program is the set of meticulous, step-by-step instructions that tell a system precisely what to do so that it will accomplish a specific task. How you want the computer to get from start to finish—essentially, a set of rules—is the “algorithm.” Machine learning programs run on neural networks and analyze data in order to help computers find new things without being explicitly programmed where to look. Within the field of AI, machine learning is useful because it can help computers to predict and make real-time decisions without human intervention. 001 Deep Neural Networks (see also “Deep Learning”) Deep learning is a relatively new branch of machine learning, and it will soon be an invisible part of every organization. Programmers use special deep learning algorithms alongside a corpus of data—typically many terabytes of text, images, videos, speech and the like. The system is trained to learn on its own. While con- ceptually, deep learning isn’t new, what’s changed recently is the amount of compute power and the volume of data that’s become available. In practical terms, this means that more and more human processes will be automated. Including the writing of software, which computers will soon start to do themselves. 002 Real-Time Machine Learning It is recently possible to use a continual flow of transactional data and adjust models in real-time. Potential use cases include: matching customers to the right product as they are looking at a website, re-writing content on a site to match the needs of each individual user, real-time fraud detection, and security measures such as authenticating someone based on her typing habits. TRENDS 001 - 013 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action 35 HBO’s new series Westworld contemplates a world in which artificially intelligent humanoids are built for our amusement.

36. 36 © 2017 Future Today Institute TRENDS 001 - 013 006 Generative Algorithms For Voice Researchers at MIT are studying how children learn new words in order to train computers on automatic speech recognition. As humans, we are able to master a new concept from just one or two examples; for machines, this is a more diffi- cult task when it comes to language. In the coming year, we expect to see more research emerging in this area. 007 Generative Algorithms For Sound MIT’s CSAIL researchers have trained computers to watch videos and predict corresponding sounds in our physical world. For example, what sound is generated when a wooden drumstick taps a couch? A pile of leaves? A glass windowpane? The focus of this research is to help robots understand how objects interact with each other in the physical realm. But future versions of the algorithms could be used to automatically produce sound and sound effects for news videos, mov- ies and TV shows. It also raises the specter of audio fraud—what happens when computers are able to spoof our voices and natural sound? 008 Zero-Knowledge Proofs With all of the hacking scandals that have plagued us in the past few years, smart businesses and organizations are turning to zero-knowledge proofs, which allows one party to verify data without conveying any additional information (like how or why the mathematical statement is true). In essence, this eliminates the need for a company to store private identity data during the verification process. Ze- ro-knowledge proofs aren’t new, but deploying them to protect our credit cards 003 Image Completion If a computer system has access to enough images—millions and millions—it can patch and fill in holes in pictures. There are practical applications for amateur photographers: if the foreground of a mountain is out of focus, another version of the scene can be swapped in to generate the perfect picture. Image completion is also a useful tool for law enforcement and military intelligence officers—computers can now assist them in identifying who or what is in the frame. 004 Predictive Machine Vision Researchers at MIT’s CSAIL have trained computers to not only recognize what’s in a video, but to predict what humans will do next. Trained on YouTube videos and TV shows such as “The Office” and “Desperate Housewives,” a computer system can now predict whether two people are likely to hug, kiss, shake hands or slap a high five. This research will someday enable robots to more easily navigate human environments—and to interact with us humans by taking cues from our own body language. 005 Natural Language Generation Algorithms can transfer data into a narrative using natural language generation. Dozens of news and other organizations, including Bloomberg and the Asso- ciated Press, are using Automated Insights, which mines data and is capable of writing more than 2,000 stories per second. They will use natural language generation to produce stories about fantasy football, earnings reports and the like. Narrative Science employs its NLG system to build narratives out of big data sets and to help non-data science people make better sense of what’s happening within their organizations. Artificial Intelligence cont. © 2017 Future Today Institute In the near-future, we won’t write code for computers. Instead, we’ll train them like dogs. 36

37. 37 © 2017 Future Today Institute TRENDS 001 - 013 010 Algorithm Marketplaces Most organizations can’t staff a team of developers who have unlimited time to create, test and refine algorithms. As a result, communities of developers are offering up their algorithms in emerging algorithm marketplaces. Algorithmia and DataMapper are a sort of Amazon for algorithms, where developers can upload their work to the cloud and receive payment when others pay to access it. DataXu offers a marketplace for its proprietary algorithms. PrecisionHawk has launched a marketplace for predictive agriculture algos. A number of other networks, such as Nara Logics, MetaMind, Clarifai offer tools for developers to build deep learning into any application. Look for even more niche marketplaces in 2017. 011 Pre-Trained AI Chips A number of companies, including IBM, Google, Intel and Movidius, are working on extremely powerful chips, and some come pre-trained. In short, this means that the chips are ready to work on AI projects. Google’s chip is called a Tensor Processing Unit (or TPU), and was specifically built for the deep learning branch of AI. It is designed to work with the company’s TensorFlow system. For reference, TPUs are what was used in the famous AlphaGo match between Goog- le’s DeepMind system and a world Go champion. Marketing pre-trained chips to businesses will speed up commercialization and as a result will further R&D. and online identities is an emerging application. Irish startup Sedicii recently launched its zero-proof software, which promises to reduce fraud. Researchers at Microsoft and Princeton University are working on a zero-knowledge proof so that inspectors can identify something as a nuclear weapon without requiring them to take it apart, which would spread information about how to build one. 009 Algorithmic Personality Detection Marketers will soon have access to algorithms that can assess your personality and predict your specific needs and desires. Nashville-based startup Crystal and IBM’s Personality Insights both use social data and will rewrite everything from emails to resumes based on each of your intended recipients. Meanwhile, some life insurance underwriters are attempting to assess your personality—via your magazine and website subscriptions, the photos you post to social media, and more—in order to determine how risky an investment you are. Some lenders have used personality algorithms to predict your future financial transactions. (The data show that if you look at two people with the same professional and personal circumstances, the one with a higher college G.P.A. will be more likely to pay off a debt.) Algorithms will harness your data in order to assess your predicted success at work, how likely you are to bounce around jobs and more. Artificial Intelligence cont. © 2017 Future Today Institute Algorithmia is a marketplace for algorithms. 37

38. 38 © 2017 Future Today Institute TRENDS 001 - 013 Researchers at a number of universities—including Carnegie Mellon, MIT, Prince- ton, University of California-Berkeley, International Computer Science Insti- tute, among others—have started to discover unintended, but explicit bias in algorithms. In 2016, Google was shown to display high-income job ads to men six times more often than women, while searching for “C.E.O.” in Google Images returned 89% men. (As of October 6, 2016, the first instance of a woman was actually a marketing photo for the CEO Barbie doll.) Part of the problem has to do with the building blocks of AI: computers are trained using a limited initial set of data, and the training programs are built by humans. Often, the training sets reveal unacknowledged bias hidden within us. So if the training data predominantly shows white male CEOs, algorithms won’t recognize people who look different. How can we push the limits of data and algorithms without accidentally creating future socio-economic, religious and ethnic divides? 012 Uncovering Hidden Bias in AI Every single day, you are creating unimaginable amounts of data, both explicitly (uploading and tagging photos on Facebook) or implicitly (searching online for cooking utensils, cars, or doctors). That data is mined and used, often without your direct knowledge or understanding, by algorithms. It is used to create advertising, to help potential employers predict our behaviors, to determine our mortgage rates and even to help law enforcement predict whether or not we’re likely to commit a crime. In May 2016, ProPublica.org published an exceptional investigation on machine bias and the problem of using AI to predict future crim- inals. Their findings: so-called “risk assessment” software is increasingly common in courtrooms across the nation, and it is used to inform decisions about everything from bond amounts to the length of a criminal sentencing. Perhaps unsurprisingly, the software is biased against black people. (We encourage you to read ProPublica’s full report: https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.) As of October 6, 2016, the first instance of a woman returned for “CEO” in a Google Images search was a marketing photo for the CEO Barbie doll. Artificial Intelligence cont. Needs Monitoring Informs Strategy Requires Action © 2017 Future Today Institute38

39. 39 © 2017 Future Today Institute Artificial Intelligence cont. Needs Monitoring Informs Strategy Requires Action TRENDS 001 - 013 013 Accountability and Trust We will soon reach a point when we will no longer be able to tell if a data set has been tampered with, either intentionally or accidentally. AI systems rely on our trust. If we no longer trust the outcome, decades of research and technological advancement will be for naught. Leaders in every sector—government, business, the nonprofit world and so on—must have confidence in the data and algorithms used. Building trust and accountability is a matter of showing the work performed. This is a complicated process, as understandably corporations, government offices, law enforcement agencies and other organizations want to keep data private. Committing to transparency in method would create trust without necessarily divulging any personal data used. In addition, hiring an ethicist to work directly with managers and developers, as well as greatly diversifying the pool of developers to include people of different races, ethnicities and genders will solve for inherent bias in AI systems. © 2017 Future Today Institute Trust and accountability are important trends within AI in 2017. 39

40. © 2017 Future Today Institute Bots Second year on the list Key Insight You’ve no doubt heard of a bot: a software application that’s been designed to automate certain tasks, such as scheduling or managing basic customer service requests. In the past year, bots have emerged from the fringe and have started to enter our mainstream vocabulary. There are now 12,000 Facebook Messenger bots available, as well as a number of platforms that make it easy for anyone to build a bot. Examples In the 1960s, Joseph Weizenbaum wrote a computer program called Eliza that was capable of simulating a conversation between a psychiatrist and patient. It offered up plausible responses to common questions. In March 2016, the world watched as @Tai.ai, a Microsoft experimental Twitterbot, went on an anti-Semitic, homophobic, racist rampage within 24 hours after its ﬁrst tweet. What’s Next Many brands you recognize (1-800-Flowers.com, Pizza Hut and Dutch airline KLM) are using chatbots for marketing and customer service. Disney partnered with bot developer Imperson to deploy character bots, including Miss Piggy. Tai.ai was built on the same platform as Microsoft’s experimental Mandarin-language bot, Xiaoice. Both were capable of intimate conversations with users, because the program is able to remember details from previous conversations and because it mined the Internet for human conversations in order to synthesize chat sessions. The key difference: Xiaoice was released in a country where citizens carefully guard their activity online, while Tai.ai was born into America’s free-wheeling internet. During the recent campaign cycle, we witnessed the rise of botnets—networks of computers designed to send out spam. Fake social media accounts, many of which originated in Russia, artfully tricked people into having arguments about everything from Donald Trump to immigration to taxes. The intelligence community should deploy bots for surveillance and for digital diplomacy. HR managers can use bots to train employees. Meantime, as Slack continues to grow in scale and popularity, bots within that environment will help automate meetings and status updates and more, saving time and increasing productivity. Watchlist Russia; Weibo; WeChat; Alphabet (Google); Snapchat; China; Microsoft; Chatfuel; Pandorabots; Twilio; Amazon; Facebook; Slack The Tay.ai Twitter bot went on a homophobic, sexist, racist, anti-Semitic bender within 24 hours of its launch. TREND 014 40 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

41. 41 © 2017 Future Today Institute We are training bots in our own image. When developing your bots in 2017, we recommend that you rate your work before deployment. Use this scale to rate your bot on its effectiveness—and to determine, in advance, whether or not you’ve accidentally encoded bias into your system. Rate your bot on a scale of 0 - 10, with 10 being the highest (and preferred) score The Botness Scale 01 Is your bot’s purpose explicit? Will people interacting with your bot clearly understand what its purpose is after the ﬁrst few interactions? 02 Does your bot perform its designated function well? 03 Is your bot easy to access, either on a designated platform or across platforms? 04 Is it intuitive and easy to use? 05 Does your bot help people learn something new, or does it effectively reinforce something that people already know? 06 Does your bot provide people with the necessary context to have a good conversation? 07 Does the corpus (the initial, base set of questions and answers) you’ve created reﬂect only one gender, race or ethnicity? If so, was that intentional? 08 Did you assign your bot a traditional gender, ethnic or racial identity? If so, does it reference any stereotypes? 09 Does your bot respond to gendered or sexist remarks? Does it respond to racial epithets or religious slurs? If it does respond, are the responses appropriate to people of the group targeted? 10 Does your bot help people learn about their own biases or broaden their worldviews? © 2017 Future Today Institute

42. © 2017 Future Today Institute Deep Learning Second year on the list Key Insight Programmers use special deep learning algorithms alongside a corpus of data— typically many terabytes of text, images, videos, speech and the like. The system is trained to learn on its own. Examples Deep learning is a relatively new branch of machine learning. The Oregon Trail was easy for anyone to play because a person created the game, and he only included straightforward choices and outcomes. But in real life, during 1810 - 1840, the Oregon Trail presented more threats than what was in the game: there were an infinite amount of variables to consider, which means an unknowable number of possible outcomes. This is a problem for deep learning. Theoretically, an artificially intelligent machine could be trained to learn how to survive on the Oregon Trail, even with such a high number of details to consider. Meanwhile, in early 2016, Google’s AlphaGo—an AI program—beat a professional Go player 5-0. The great hope of those working in AI is that someday, deep learning will have advanced enough not just to make better decisions in a challenge like the Oregon Trail, or to beat a human at Go—but to interact with us such that they’re indistinguishable from other people. Except that their artificial neural networks are orders of magnitude more powerful than the biological neural networks inside our heads. What’s Next Deep learning isn’t just used by Google, though researchers on the DeepMind team are working on a host of applications for neural networks. Internet searching will be aided by deep learning—we’ll have conversations and get to our desired answers far more quickly than we do today searching through pages of content. Chip designers at Fujitsu and Intel are using deep learning to design smaller, faster systems. Scientists at the Karlsruhe Institute of Technology developed a deep neural network that can automatically identify people’s faces using infrared cameras—law enforcement will soon be able to see as clearly in total darkness as they can in the bright daylight. DeepEar was developed by Bell Labs and is a neural network that listens via our smartphones without draining our batteries. Facebook is using this technology to automatically generate faceprints—which is like a fingerprint, but using our photos instead. (The U.S. doesn’t yet have biom- etric data protection laws.) We recommend that you download your Facebook file if you haven’t already, as this will give you an indication of what data Facebook is storing and how it relates that information across user profiles. Qualcomm is developing neuromor- phic chips, which have been used in robots to help them recognize objects they haven’t seen before, or navigate themselves to a new location. In 2017, experi- mentation in deep learning will begin to lay the groundwork for all that’s to come. Watchlist Baidu; IBM; Stanford’s AI Lab and Vision Lab; MIT’s CSAIL; Google; Amazon; Mi- crosoft; Fujitsu, Facebook; Karlsruhe Institute of Technology; Bell Labs; University of Toronto; University of California - Los Angeles, University of California - Berke- ley; NSA; Qualcomm Google’s DeepMind challenge a champion Go player to a game—and won. TREND 015 42 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

43. © 2017 Future Today Institute Cognitive Computing Fifth year on the list Key Insight This trend has evolved from a key idea in our 2010 trend report: anticipatory computing. Cognitive computing systems use natural language processing and artificial intelligence in order to understand our intentions. Examples By now, you will have heard of IBM’s Watson platform, a system that uses natural language processing and machine learning to enable people and machines to interact more naturally. Cognitive systems like Watson super-charge our human ability to think through complex problems. Watson is assisting doctors, scientists, engineers, lawyers and other professionals now in their everyday work. For example, in August 2016, doctors in Tokyo were treating a patient who met all of the criteria for acute myeloid leukemia, a blood cancer. After treatment, her re- covery was unusually slow, and doctors began to wonder if there was something else wrong. Yet their reading of the patient’s medical data kept pointing to acute myeloid leukemia. They fed the patient’s data into Watson, which crunched her genetic data against a larger corpus of data. Ten minutes later, Watson offered a set of new diagnoses, which included acute myeloid leukemia but also showed a strong possibility of a rare secondary leukemia. Doctors changed the woman’s treatment plan, and within just a few weeks she was in remission. What’s Next Late in 2016, IBM launched the Cognitive Horizons Network, which is a collaborative network dedicated to accelerating the field of cognitive computing. Those schools include: Rensselaer Polytechnic Institute, Massachusetts Institute of Technology, the University of Illinois at Urbana-Champaign, the University of Maryland, Baltimore County, the University of Michigan, and the University of Montreal. AI researchers at member schools will share resources and work jointly on cognitive problems. Meanwhile, Watson is learning how to read and interpret medical images—a job that was previously reserved for highly-trained radiolo- gists. One interesting offshoot: a cognitive system could read all of the other data captured in a medical image, making the image far more valuable to a patient’s record. Watson and CVS have partnered to learn about patients and their medical histories in order to red-flag problematic behaviors, potentially transforming the role of your local pharmacist. Working together with Watson, your local pharmacist may begin to offer you holistic advice and interventions. IBM is now developing advanced data-centric supercomputing systems that will embed compute power everywhere data resides in a system, which means a convergence of analytics, modeling, visualization, and simulation, and driving new insights at very fast speeds. In 2017, IBM will make its big push into a number of fields, including finance, journalism, retail and healthcare, part of which includes better patient access to their own health and prescription history. Watson—and for the time being, your doctor—will see you now. Watchlist IBM Research, Cognitive Horizons Network IBM’s Watson is a cognitive computing platform. TREND 016 43 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

44. © 2017 Future Today Institute Smart Virtual Personal Assistants (SVPAs) Third year on the list Key Insight Smart Virtual Personal Assistants use semantic and natural language processing, along with our data, in order to anticipate what we want or need to do next...even before we know to ask. You already have an SVPA in your phone, and you’ll have one in your kitchen or living room soon. Examples If you’ve ever used Siri, Google Now or Amazon’s Alexa, you’re familiar with SVPAs. They have nearly invisible interfaces and are being further designed so that you talk, conversationally, with them. Most of the earlier SVPA apps have now been acquired. Emu was acquired by Google, Donna was acquired by Ya- hoo, Cue was acquired by Apple...and the list goes on. When it was still ac- tive, Emu was a clever stand-in for a personal secretary. It would monitor the conversation and automatically make suggestions as two people texted. If you asked your friend to see a movie, Emu would immediately geolocate both of you, suggest a nearby theater and show ﬁlms and times, then check your calen- dars for your availability. It would even display a preview for you to watch. Once it determined the best time for you to meet, it would help you purchase tickets and enter all the data into your calendar. And it did all of this inside a single mobile application. This illustrates what to expect soon. According to what we’ve learned from product teams throughout the tech industry, a new wave of virtual assistants will continue to surface in the coming year. What’s Next SVPAs will become more pervasive in 2017. There are a number of devices launching in the coming year. Watch for Alexa-like products from Alphabet and Apple. In addition to hardware, you’ll ﬁnd a number of SVPA apps coming to market that will help you do everything from schedule appointments to feed you real-time information as you watch news programs. You’ll also see SVPAs hidden throughout other connected devices, such as your home thermostat, your refrigerator and your phone. Researchers at MIT, Stanford, and the University of Texas at Austin are building infrastructure so that our devices will be able to listen and watch: They’ll know the places we go, the people we interact with, our habits, our tastes and preferences, and more. Then they’ll use this data to anticipate our needs. Marketers, credit card companies, banks, local government agencies (po- lice, highway administration), political campaigns and many others can harness SVPAs to both surface and deliver critical information. Watchlist Stanford University; MIT; University of Texas at Austin; Amazon; Apple; Alphabet; Microsoft; Yahoo; Robin Labs; IBM. Amazon’s Echo is an SVPA for your living room. TREND 017 44 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

45. © 2017 Future Today Institute Ambient Interfaces Second year on the list Key Insight Ambient music pioneer and visionary Brian Eno wrote in his liner notes for Music for Airports: “Ambient music must be able to accommodate many levels of listening attention without enforcing one in particular; it must be as ignorable as it is interesting.” Our modern interfaces are becoming more and more like ambient music—able to do more for us with fewer direct actions, yet still able to captivate our attention. Examples If you’ve interacted with Google Now or Amazon’s Alexa, or if you own a smart- watch, you’ve used an ambient interface. It listens—ﬁguratively and literally—and automatically delivers you the information you need to know, just as you need to know it. What’s Next In our modern age of information, the average adult now makes more than 10,000 decisions a day: some big, like whether or not to invest in the stock market, and some small, like whether to glance at your mobile phone when you see the screen light up. What makes ambient design so tantalizing is that it should require us to make fewer and fewer decisions in the future. Think of it as a sort of autocom- plete for intention. Our mobile devices and many of the wearables coming to market will be listening and observing in the background and will offer up either text, audio or haptic notiﬁcations as needed, and those will be decided by algorithm. In 2017, we expect to see even more ambient interfaces being embedded into productivity software and apps, tools used by law enforcement, customer loyalty apps, news apps and gaming systems. Watchlist Alphabet (Google); Amazon; Apple; Microsoft; Spotify; Mumble; IFTTT; Samsung Google Home’s ambient interface delivers you just the information you need, whenever you need it. TREND 018 45 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

46. © 2017 Future Today Institute Deep Linking Third year on the list (non-consecutive) Key Insight Deep mobile linking has been around since the beginning of smartphones. Deep mobile links make it easier to find and share data across all of the apps in your phone. Examples There are three kinds of deep links: traditional, deferred and contextual. Tradition- al deep links reroute you from one app or site (such as a link posted in Twitter) directly to the app, as long as you have that app installed. Deferred deep links either link straight to content if the app is installed, or to an app store for you to download the app first. In 2016, we saw the proliferation of deep linking throughout the Apple and Android operating systems. Contextual deep links offer much more robust information—they take you from site to app, app to site, or app to app, and they can also offer personalized information. For example, when you land at the airport, you might find that your airline app sends you a link to Uber. (You’ll find similar offerings within Google Maps.) Apple’s iOS10 enables quick switching and sharing between apps via deep links. What’s Next This interoperability signals a new shift in thinking, as many mobile app developers have been hesitant to use deep links. With Google and Apple’s changes, app-to-app experiences should start to become more common. For example, Branch is a startup that helps developers deliver previews of their applications before users install them. We expect to see this trend develop as the deep linking ecosystem starts to take off in the coming year. Watchlist Button; Google; Apple; Branch; MobileDeepLinking.org; Deeplink.me; Quixey; Appsfire; AdRoll; tapCommerce; Vungle; InMobi; MoPub; Vserv Like Uber, many platforms are now offering deep mobile links. TREND 019 46 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

47. © 2017 Future Today Institute Consolidation in AI First year on the list Key Insight All of the recent enthusiasm for AI has led to a number of startups—along with lightening-fast acquisitions. Some now worry that the still nascent field of AI is already under the direction of too few companies. Examples In the past year, Apple has bought Seattle-based AI startup Turi for $200 million, but it isn’t the only company shopping around. To date, the top acquirer of AI startups includes Google, Twitter, Apple, Intel, Salesforce, AOL and IBM, in that order. What’s Next As with any technology, when just a few companies dominate the field, they tend to monopolize both talent and intellectual property. This isn’t necessarily bad, but when it comes to the future of AI, we should ask whether consolidation makes sense for the greater good, and whether competition—and therefore access—will eventually be hindered as we’ve seen in other fields such as telecommunications and cable. Watchlist Alphabet (Google); Apple; Microsoft; Intel; Salesforce; AOL; IBM; Facebook; Am- azon. Consolidation has begun within AI. TREND 020 47 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

48. © 2017 Future Today Institute Human-Machine Interfaces Second year on the list Key Insight Researchers are finding new ways to connect humans and mammals directly to computers. With these human-machine interfaces, people can communicate via thought alone. Which promises new options for those suffering from stroke and paralysis. Examples At the University of Washington’s Center for Sensorimotor Neural Engineering, researchers built a system allowing one person to transmit his thoughts directly to another person. Using electrical brain recordings and a form of magnetic stim- ulation, one researcher sent a brain signal to another person elsewhere on cam- pus, causing his finger to tap a keyboard. Meanwhile, researchers at the Center for Neuroengineering at Duke University have built a real-life Iron Man suit, allowing a young man suffering from complete paralysis of his lower body to walk out onto a soccer field and kick the first ball of the World Cup. What’s Next The team at Duke is now working on a so-called “Brainet,” which connects the brains of a group of mammals to harness and direct their neural activity. One successful experiment: to see if networking rats together would allow researchers to solve a basic forecasting problem that individual rats struggled to complete on their own. In every trial, the Brainet successfully solved the problem, and per- formance improved the more the rats worked together. This work has a practical and altruistic purpose: to help victims of stroke or traumatic brain injury regain their cognitive abilities and motor function. Rather than having to relearn, they need only reload those memories. Watchlist Duke University’s Center for Neuroengineering; University of Southern California; University of Washington’s Center for Sensorimotor Neural Engineering; Johns Hopkins University; Carnegie Mellon University; Starlab; Case Western Reserve University; Penn State University; Johns Hopkins Applied Physics Laboratory; DARPA. Dr. Miguel Nicolelis and his team of researchers at the Center for Neuroengineering at Duke University are researching how to connect our brains to machines. This brain-controlled car is being operated by a rhesus monkey, whose brains are similar to ours. TREND 021 48 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

49. © 2017 Future Today Institute Smart Dust First year on the list Key Insight These are computers, no larger than a grain of dust, that are light enough they can suspend in the air. (Or in your brain.) Examples For years, researchers have been hard at work on miniaturization, as they try to shrink computers as much as possible, down to the size of sand or dust. Each particle-computer consists of circuits and sensors capable of monitoring the environment, and even taking photographs. Scientists at the University of Califor- nia Berkeley developed what they call “neural dust,” which are microscopic computers that work alongside remote ultrasound to send and receive data about the brain. Meanwhile, researchers at the University of Stuttgart ﬁgured out how to print tiny 3D lenses—120 millionths of a meter in diameter, or about the size of a grain of sand. What’s Next Researchers believe that this technology will dramatically change our approach to medical imaging. Rather than relying on our current endoscopic technology, which is bulky and invasive, a patient could simply inhale smart dust. Beyond medicine, trillions of smart dust particles could be released in the wind to meas- ure air quality or take photos. But we must also consider other use cases: would you know if you’d inhaled rouge smart dust on a windy day? In the farther-future, could this technology be used to track us surreptitiously? Watchlist University of Stuttgart; University of California Berkeley; Stanford University; Uni- versity of Washington; Purdue University; USC Robotics Research Lab; DARPA. The University of Stuttgart’s multi-lens system next to a single doublet lens. TREND 022 49 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

50. © 2017 Future Today Institute Soft Robotics First year on the list Key Insight This is a relatively new ﬁeld of robotics research. Imagine robots that are squishy and can operate in unpredictable environments. Examples Scientists at the BioRobotics Institute at the Scuola Superiore Sant’Anna in Pisa, Italy, have been investigating soft robotics. Recently, they created a robot octopus, capable of replicating the animals’ agile motions. In order to replicate the biology of an octopus, they built computer models using exact measurements and then experimented with a number of soft actuators to develop artiﬁcial muscles. Researchers at Worcester Polytechnic Institute have been working on a robotic snake. What’s Next Soft robots mean that someday soon, we will be able to enter and explore environments previously unreachable by conventional methods: deep ocean waters, the terrain of Mars, and perhaps even the gushing rivers of blood inside our own bodies. This is just the beginning. Don’t expect to play with a squishy robot drone at your next pool party. However those who follow drones, robotics, infrastructure and defense should have new prototypes to look at in 2017. Watchlist Scuola Superiore Sant’Anna; Worcester Polytechnic Institute; MIT Media Lab; Johns Hopkins Applied Physics Laboratory; DARPA. This octobot is an example of a soft robot. TREND 023 50 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

51. © 2017 Future Today Institute Robot Companions First year on the list Key Insight After many years being developed inside of R&D labs, we are now starting to see the first generation of robot companions emerge. Examples Many countries, including Japan, Italy, and Germany, will soon face rapid demographic shifts. In Japan, one in four people are now age sixty-five or older—there aren’t enough people working to support both retirees and children. Science and technology will eventually stand in for the lack of people: robots will assist with everything from elder care, to medical assistance, to everyday companionship. Unsurprisingly, this first generation of companion robots is being built in Japan: Toyota is launching its Kirobo Mini companion, while Sharp has already debuted its RoboHon. When SoftBank’s Pepper went on sale at the very end of 2015, the company sold all 1,000 units in under a minute. What’s Next Within a generation, there will not be enough people to make Japanese society work as it does today—but Japan isn’t alone in its demographic shift. Many in- dustrialized countries, including the U.S., could suffer the same fate. For those concerned that AI and robots will take away jobs, that doesn’t necessarily take into consideration that we already didn’t have enough citizens ready to do the work on their own. Anyone interested in the future of robotics would be wise to look not to Silicon Valley, but instead to universities and R&D labs in Japan, where extensive research on the next generation of robot companions is already underway. Out of necessity, robots—mechanical systems, artificial intelligence, and automated services—will act as productive, emotionally-intelligent stand-ins for a younger generation that was simply too small in numbers. Watchlist SoftBank; Sharp; Toyota; MIT Media Lab; Buddy; Nanyang Technological Universi- ty; Sony; Tokyo University; Johns Hopkins Applied Physics Laboratory; Pepper is a robot companion from Japan’s SoftBank. TREND 024 51 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

52. © 2017 Future Today Institute Collaborative Robots First year on the list Key Insight Robots that communicate in real-time and cooperate on projects make a strong team. Examples Teams of robots are now capable of working together, and they’re efﬁcient, since not every single robot has to excel at every task. Researchers at Carnegie Mellon University have built collaborative robots that are designed to work together. In their recent work, a robot named Baxter is stationed at a table working on a project. Once completed, another robot on the team—CoBot—picks up the item and hands it to a human. Teams of collaborative robots can communicate to each other, on their own, about when to wait, when to move, to carry out an activity, or even to ask what to do. What’s Next Use your imagination and you can probably see what’s on the horizon. Collabora- tive robots will play a key role in automating the tasks performed in warehouses, manufacturing plants, logistics and delivery services. They will also run operations in conﬂict zones. Watchlist Carnegie Mellon University; MIT’s Interactive Robotics Group; DARPA; Auton- omous Solutions; Energid Technologies; Boston Dynamics; Alphabet (Google); Amazon; ABB Robotics; Aethon Inc.; FANUC Robotics; EPSON Robotics; Seegrid; SoftBank Robotics Corporation; Toyota; ULC Robotics; VEX Robotics; Yamaha; University of Tokyo; Johns Hopkins Applied Physics Laboratory Self-assembling swarming microbots developed at MIT. TREND 025 52 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

53. © 2017 Future Today Institute Ethical Manufacturing First year on the list Key Insight Could robots bring the end of forced labor and lead a new era of ethical manufacturing? Examples Recent advancements in robotics are proving that soon, humans may no longer be required to perform labor-intensive manufacturing jobs. While this certainly means that people will be out of certain kinds of work, it does imply the end of bonded, forced and child labor—not to mention slavery—which unfortunately has become commonplace in places like China, the Philippines and Bangladesh. In October 2016, a Canadian court allowed a lawsuit brought by Eritrean workers against Nevsun Resources, a mining company: it was the first time in history that a tort claim for modern slavery went ahead in Canada. Meanwhile, in September, the Associated Press published a searing account of foreign fishing workers, con- fined and forced to work on U.S. fishing boats. The AP’s investigation revealed a disturbing present-day reality: men are forced to use buckets instead of toilets, suffer sores from bed bugs and don’t have enough food to sustain them. What’s Next Look for a number of new advancements in robotics that further reduce the need for human labor, such as the Sewbo, which is similar to a traditional sewing machine but also has a smart robotic arm, allowing it to both sew and assemble an item of clothing. Elon Musk’s giant Gigafactory will soon employ hundreds of robotic arms and “automated guided vehicles,” essentially mobile robots that transport items from one area to another. There could be models available for the future sooner than you might think. Manufacturing regions, like Ohio and Michi- gan, could find their workforces disrupted. Watchlist National Association of Manufacturers; Alliance For American Manufacturing; Te- sla; Sewbo; Carnegie Mellon University; MIT’s Interactive Robotics Group; Alpha- bet (Google); Amazon; ABB Robotics; Aethon Inc.; ULC Robotics. Factories staffed with robots could mean the end of harsh working conditions. TREND 026 53 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

54. © 2017 Future Today Institute Universal Basic Income First year on the list Key Insight An unconditional, guaranteed income for everyone within a country—a concept made popular in the 1960s—is being debated once again in the wake of automation, advanced robotics and artiﬁcial intelligence. Examples The origins of universal basic income (UBI) date back to Thomas Paine who, in a 1797 essay, theorized that governments should pay citizens £15 a year. There have been a number of universal basic income (UBI) experiments. In the 1970s, the Ca- nadian province of Manitoba began sending UBI checks to all of its residents. An economist analyzed the program, which only lasted a few years, and discovered that life improved signiﬁcantly: kids stayed in school, fewer people wound up in the hospital, and many reported that their quality of life overall was better. UBI has had its share of supporters throughout history, from Dr. Martin Luther King, Jr., to the Nixon Administration, to far-right economist Milton Friedman. What’s Next Finland has just launched a two-year UBI pilot study. A randomly-selected group of 2,000 - 3,000 citizens will begin receiving a monthly stipend of 560 Euros (or about $600 dollars.) Y-Combinator, the storied Silicon Valley incubator of hot tech startups such as Reddit, Wufoo and Rapportive, is sponsoring a UBI program in Oakland, California. In June 2016, Swiss voters rejected a UBI initi- ative guaranteeing citizens around $2,500 a month. Critics of UBI argue that if citizens are simply handed a wad of cash each month, they won’t spend it on preventative health or nutritious food, and that they will be less inclined to work. Proponents say that our fast-approaching robotics era will render many out of work anyway—and that a UBI will help insure our country against an imminent implosion in the job market. Watchlist Stanford Center for Philanthropy and Civil Society; White House Council of Eco- nomic Advisors; American Enterprise Institute; Oxford University’s Carl Benedikt Frey and Michael Osborne; Finland; Netherlands; Norway; Sweden; Organization for Economic Co-operation and Development. TREND 027 54 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action A UBI would guarantee income for everyone.

55. © 2017 Future Today Institute Artificial Intelligence in Hiring First year on the list Key Insight Researchers are finding that the usual data sources—test scores, GPAs and the like—aren’t reliable indicators of talent. Examples Artificial Intelligence is being used to assess personal attributes like empathy, thoughtfulness, engagement, motivation and drive. Coupled with social media screening—looking at an applicants previous posts on Facebook, Twitter, Insta- gram, blogs and elsewhere online—emerging systems consider both personality and behavior when evaluating possible new hires. Companies like RoundPegg and Interviewed, which collect data and perform assessments on candidates, are being used by high-profile clients including ExxonMobil, Xerox and Razorfish. What’s Next One likely future benefit of AI-assisted hiring is that machines—theoretically, at least—can be more objective than people. However, as we start to rely more on these systems, we must also redouble our efforts to ensure that the algorithms and data used aren’t also subject to bias. After all, these systems were originally envisioned, architected and programmed by humans. Watchlist Mya A.I.; Recruit Strategic Partners; HackerRank; LinkedIn; IBM Watson; Alphabet (Google); Facebook; University of Oxford’s Martin Programme on the Impacts of Future Technology; Xerox; Razorfish; ExxonMobil; RoundPegg; Interviewed. AI-assisted hiring could reduce bias and diversity workforces. TREND 028 55 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action

56. © 2017 Future Today Institute Productivity Bots Second year on the list Key Insight Productivity Bots will help assist workers and students perform tasks more efﬁ- ciently. Examples Slack is a popular hybrid instant message/ email system that lets you sort and tag, search, and choose to broadcast messages to your whole team or just to a few members. The average Slack user spends around 140 minutes (nearly two and a half hours) per weekday on the service, and much of the reason is because Slack bots can automate myriad productivity services on their behalf. For example: you can automatically retrieve and read news from multiple sources, set work and break timers, plan meetings and events for a few staff without spamming an entire team and collaborate on Google docs. Productivity bots are now offered in a number of different ofﬁce apps, including Yammer, HipChat and Skype. What’s Next Slack’s success has inspired numerous startups and competitors, including Mi- crosoft, which introduced its own product late 2016. We should expect deeper integrations across all platforms and services in 2017, which should promise even more increased productivity. Watch for more automated features within Trello, Dropbox, Google Drive, Heroku, Mailchimp and Zendesk, to name a few. Watchlist Slack; Alphabet (Google); Yammer; HipChat; Skype; Trello; Dropbox; IFTTT; Hero- ku; Y Comibinator; Mailchimp; Zendesk; Microsoft. Slack is a popular platform that now includes bot assistants. TREND 029 56 © 2017 Future Today Institute Needs Monitoring Informs Strategy Requires Action