The document discusses how automation and AI will change the nature of work. It argues that most jobs will be redesigned to take advantage of both machine strengths like speed and accuracy as well as human strengths like creativity and judgment. New roles will emerge that facilitate the implementation of automation or use AI to augment human capabilities. Overall, automation tends to raise prosperity by taking over routine tasks while leaving more complex problems for humans. The document outlines different types of human-machine collaboration and how design careers in particular may be transformed by pairing creative human skills with AI's ability to analyze large datasets and generate new ideas.
Not only do we overestimate how easy it is to replace humans, replacing them is often neither desirable nor the best use of AI. A better way to think about the future of AI is interlacing its strengths with those of humans.
Autonomous vehicles are often posed as reducing human interaction with vehicles to a minimum. While they will take more of the cognitive load of driving off humans, in many cases it is more useful to think of a human-machine collaboration.
We forget that when technology destroy, it helps us to create new ones, as long as we remember that the point isn't just cost-reduction, but doing things that were previously impossible! That means both solving hard problems, and pairing technology with people in ways that play to the strengths of each. My keynote at Strata+Hadoop World London, May 2017.
My talk for TechStars at Techweek Kansas City in October 2018. While this is a talk based on my book WTF?, it is fairly different from many of the others that I've posted here, in that it focuses specifically on parts of the book that contain advice for entrepreneurs, rather than on the broader questions of technology and the economy. As always, look at the speaker notes for
My plenary talk to the California Workforce Association Conference in Monterey, CA, on September 5, 2018. I talked about the role of technology to augment people rather than replace them from my book WTF? What's the Future and Why It's Up to Us, and my ideas about AI and distributional economics, in the context of today's education and workforce development systems. I also summarize some of the work Code for America has been doing on the current state of the California Workforce Development ecosystem.
Towards a New Distributional EconomicsTim O'Reilly
A talk I gave on December 1, 2017 for a workshop on AI and the future of the economy organized by the OECD and the Berkeley Roundtable on the International Economy. In it, I explore implications of AI and internet-scale platforms for the design of markets, with the goal of starting a conversation about what we might call "distributional economics."
Not only do we overestimate how easy it is to replace humans, replacing them is often neither desirable nor the best use of AI. A better way to think about the future of AI is interlacing its strengths with those of humans.
Autonomous vehicles are often posed as reducing human interaction with vehicles to a minimum. While they will take more of the cognitive load of driving off humans, in many cases it is more useful to think of a human-machine collaboration.
We forget that when technology destroy, it helps us to create new ones, as long as we remember that the point isn't just cost-reduction, but doing things that were previously impossible! That means both solving hard problems, and pairing technology with people in ways that play to the strengths of each. My keynote at Strata+Hadoop World London, May 2017.
My talk for TechStars at Techweek Kansas City in October 2018. While this is a talk based on my book WTF?, it is fairly different from many of the others that I've posted here, in that it focuses specifically on parts of the book that contain advice for entrepreneurs, rather than on the broader questions of technology and the economy. As always, look at the speaker notes for
My plenary talk to the California Workforce Association Conference in Monterey, CA, on September 5, 2018. I talked about the role of technology to augment people rather than replace them from my book WTF? What's the Future and Why It's Up to Us, and my ideas about AI and distributional economics, in the context of today's education and workforce development systems. I also summarize some of the work Code for America has been doing on the current state of the California Workforce Development ecosystem.
Towards a New Distributional EconomicsTim O'Reilly
A talk I gave on December 1, 2017 for a workshop on AI and the future of the economy organized by the OECD and the Berkeley Roundtable on the International Economy. In it, I explore implications of AI and internet-scale platforms for the design of markets, with the goal of starting a conversation about what we might call "distributional economics."
We Get What We Ask For: Towards a New Distributional EconomicsTim O'Reilly
My keynote at the Venturebeat Blueprint conference in Reno, NV on March 6, 2018. The bad maps that are holding us back from building a better world. Technology need not eliminate jobs. It could be helping us tackle the world's great problems, and helping design marketplaces that ensure a more equitable distribution of the proceeds from doing so. The narrative that goes with the deck is in the speaker notes. There is also a summary and link to the video at https://venturebeat.com/2018/03/06/tim-oreilly-to-tech-companies-use-a-i-to-do-more-than-cut-costs/
Google handles over 3 billion searches a day, Amazon offers a storefront with 600 million unique items, Facebook users post 6 billion pieces of content sailing, all with the aid of complex algorithmic systems that respond to a constant influx of new data, adversarial activity by those trying to game the system, and changing preferences of users. These systems represent breakthroughs in the governance of complex, interacting systems, with algorithms that must be constantly updated to respond to rapidly changing conditions. The economy as a whole is also full of complex, interacting systems, but we still try to manage those systems with 20th century tools and processes. This talk explores what we can learn from technology platforms about new approaches that the Fed might take to improve its historical mission using the tools of agile development, big data, and artificial intelligence. My talk at the San Francisco Federal Reserve Bank FedAgile conference on November 7, 2018. Download the PPT file to read the narrative in the speaker notes. (I wish slideshare did a better job of displaying these, but they don't.)
Yet another version of my book talk, this time at Harvard Business School, on March 28, 2018. This one had fewer slides with less connecting narrative so that I could spend more time interacting with the audience. I think it went pretty well. As usual, the speaker notes contain the narrative that goes with the slides, which are mostly images.
Do More. Do things that were previously impossible!Tim O'Reilly
My keynote at SxSW Interactive on March 9, 2018. I tackle the job of the entrepreneur to redraw the map, and not to accept the idea that technology will put people out of work rather than creating new kinds of prosperity. I try to provide a call to action to throw off the shackles of the old world and to build a new one. So many companies play defense. Cut costs, watch the competition, follow best practices. Great entrepreneurs like Jeff Bezos and Elon Musk play offense. They see the world with fresh eyes, taking off the blinders that keep companies using technology to make slight improvements to existing products and practices, rather than imagining the world as it could be, given the new capabilities that technology has given us.
My talk to the joint OECD/G20 German Presidency conference on digitalization in Berlin on January 12, 2017. Fitness landscapes as applied to technology, business, and the economy. Note that the fitness landscape slides will not be animated in this PDF, which I shared this way so that you could see my narrative in the speaker notes. While it has some slides in common with my White House Frontiers conference talk, it includes a bunch of other material.
My keynote at the 2018 New Profit Gathering of Leaders conference in Boston on May 17, 2018. I talk about the lessons from technology platforms, how they teach us what is wrong with our economy, and the possibilities of AI for creating better, fairer, more effective decisions about "who gets what and why" in the economy.
My talk at the White House Frontiers Conference at CMU on October 13, 2016. I was one of the warmup acts for the President, talking about why we should embrace an AI future. Full text can be seen here
My keynote at the Open Exchange Summit in Nashville on April 18, 2018. I talk about the implications for many different kinds of companies of the fact that increasingly large segments of our economy are being dominated by algorithmically managed network marketplaces.
My keynote at OSCON 2018 in Portland. What I love about open source software, and what that teaches us about how we can have a better future by the better design of online marketplaces and the algorithms that manage them - and our entire economy. The narrative is in the speaker notes.
What's Wrong With Silicon Valley's Growth ModelTim O'Reilly
A talk I gave on the oreilly.com live training platform on January 22, 2020, focusing on the way that many Silicon Valley startups are designed to be financial instruments rather than real companies. They are gaming the financial system, much like the CDOs that fueled the 2009 financial crash. I talk about the rise of profitless IPOs, and contrast that with the huge profits of the last wave of Silicon Valley giants. In many ways, it is an extended meditation on Benjamin Graham's famous statement, "In the short term, the market is a voting machine, but in the long term it is a weighing machine."
No jobs for humans: How to survive and thrive the transition to the all robot...AJ Davis
Many experts believed driving was too complex to be automated, yet here we are with self driving taxis, cars, and trucks. The robots are coming for drivers - and they are coming for you too. No matter what your job, a robot WILL do it. They will be stronger, faster, and smarter than you. They will be better writers, better doctors, and run companies more effectively.
We can delay the inevitable by shutting down borders and subsidizing losing industries, but we will not stop robots from replacing human labor (nor should we). The challenge is in the transition from a human labor to the robot run economy. Many people will struggle to find new places for their skills, and the result could be increased income inequality, increased violence, and an uprooted sense of self.
In this talk, we’ll explore our responsibility as technologists to be aware of and address this inevitable transition to a robot labor force.
A brochure-style presentation to introduce the big picture vision for R7 Partners, a venture capital firm that finds, funds, and builds early-stage startups with ambitious innovation.
AI and its allied technolgies present an exciting scenario of job changes in coming decades. So are the concerns about loss of traditional jobs. What would be the net impact? We explore the economic models and concepts that allay unfound fears; yet warn us to be ready for constant changes and need for continuous skill rebuilding.
Five Disruptive Technologies and Their Impact on Connecticut's JobsBillKelvie
Technology disruption will cause the loss of 47% of jobs according to a recent Oxford study. This research looks at five technologies which will drive this wrenching change: Artificial Intelligence, Autonomous Vehicles, Electronic Commerce, Internet of Things and Robotics. It examines the impact on CT but is very applicable to the United States as well.
WTF - Why the Future Is Up to Us - pptx versionTim O'Reilly
This is the talk I gave January 12, 2017 at the G20/OECD Conference on the Digital Future in Berlin. I talk about fitness landscapes as applied to technology and business, the role of unchecked financialization in the state of our politics and economy, and why technology really wants to create jobs, not destroy them. (There is a separate PDF version, but some readers said the notes were too fuzzy to read.)
The AIs Are Not Taking Our Jobs...They Are Changing ThemTim O'Reilly
My talk at the Web Summit in Dublin on November 6, 2014. Reflections on the notion that AI will take away jobs, and our need to recognize and redefine the human role in the applications we build. Covers many of the same ideas as my "Internet of Things and Humans" talk, but from a slightly different angle.
But, as Musk’s above-quoted statement suggests, the rise of AI has so far occurred in a regulatory vacuum. With the exception of a few states’ passage of legislation regarding autonomous vehicles and drones, very few laws or regulations exist that specifically address the unique challenges raised by artificial intelligence, and virtually no courts appear to have developed standards specifically addressing who should But, as Musk’s above-quoted statement suggests, the rise of AI has so far occurred in a regulatory vacuum. With the exception of a few states’ passage of legislation regarding autonomous vehicles and drones, very few laws or regulations exist that specifically
address the unique challenges raised by artificial intelligence, and virtually no courts appear to have developed standards specifically addressing who should be held legally responsible if an AI causes harm.
Principles of Artificial Intelligence & Machine LearningJerry Lu
Artificial intelligence has captivated me since I worked on projects at Google that ranged from detecting fraud on Google Cloud to predicting subscriber retention on YouTube Red. Looking to broaden my professional experience, I then entered the world of venture capital by joining Baidu Ventures as its first summer investment associate where I got to work with amazingly talented founders building AI-focused startups.
Now at the Wharton School at the University of Pennsylvania, I am looking for opportunities to meet people with interesting AI-related ideas and learn about the newest innovations within the AI ecosystem. Within the first two months of business school, I connected with Nicholas Lind, a second-year Wharton MBA student who interned at IBM Watson as a data scientist. Immediately recognizing our common passion for AI, we produced a lunch-and-learn about AI and machine learning (ML) for our fellow classmates.
Using the following deck, we sought to:
- define artificial intelligence and describe its applications in business
- decode buzzwords such as “deep learning” and “cognitive computing”
- highlight analytical techniques and best practices used in AI / ML
- ultimately, educate future AI leaders
The lunch-and-learn was well received. When it became apparent that it was the topic at hand and not so much the free pizzas that attracted the overflowing audience, I was amazed at the level of interest. It was reassuring to hear that classmates were interested in learning more about the technology and its practical applications in solving everyday business challenges. Nick and I are now laying a foundation to make these workshops an ongoing effort so that more people across the various schools of engineering, design, and Penn at large can benefit.
With its focus on quantitative rigor, Wharton already feels like a perfect fit for me. In the next two years, I look forward to engaging with like-minded people, both in and out of the classroom, sharing my knowledge about AI with my peers, and learning from them in turn. By working together to expand Penn’s reach and reputation with respect to this new frontier, I’m confident that we can all grow into next-generation leaders who help drive companies forward in an era of artificial intelligence.
I’d love to hear what you think. If you found this post or the deck useful, please recommend them to your friends and colleagues!
Machine Learning: Understanding the Invisible Force Changing Our WorldKen Tabor
Readers will gain an appreciation for machine learning, and take away valuable strategies including:
• What is machine learning.
• How it’s changing the world.
• Who the major players are.
• How you can control it.
Machine learning. It’s in the news. It’s discussed in corporate boardrooms. It’s on your mind. ML algorithms seem to be at once everywhere, yet nowhere. Can we possibly understand how this invisible force is shaping our world? How will it reform your industry, and change your job?
We Get What We Ask For: Towards a New Distributional EconomicsTim O'Reilly
My keynote at the Venturebeat Blueprint conference in Reno, NV on March 6, 2018. The bad maps that are holding us back from building a better world. Technology need not eliminate jobs. It could be helping us tackle the world's great problems, and helping design marketplaces that ensure a more equitable distribution of the proceeds from doing so. The narrative that goes with the deck is in the speaker notes. There is also a summary and link to the video at https://venturebeat.com/2018/03/06/tim-oreilly-to-tech-companies-use-a-i-to-do-more-than-cut-costs/
Google handles over 3 billion searches a day, Amazon offers a storefront with 600 million unique items, Facebook users post 6 billion pieces of content sailing, all with the aid of complex algorithmic systems that respond to a constant influx of new data, adversarial activity by those trying to game the system, and changing preferences of users. These systems represent breakthroughs in the governance of complex, interacting systems, with algorithms that must be constantly updated to respond to rapidly changing conditions. The economy as a whole is also full of complex, interacting systems, but we still try to manage those systems with 20th century tools and processes. This talk explores what we can learn from technology platforms about new approaches that the Fed might take to improve its historical mission using the tools of agile development, big data, and artificial intelligence. My talk at the San Francisco Federal Reserve Bank FedAgile conference on November 7, 2018. Download the PPT file to read the narrative in the speaker notes. (I wish slideshare did a better job of displaying these, but they don't.)
Yet another version of my book talk, this time at Harvard Business School, on March 28, 2018. This one had fewer slides with less connecting narrative so that I could spend more time interacting with the audience. I think it went pretty well. As usual, the speaker notes contain the narrative that goes with the slides, which are mostly images.
Do More. Do things that were previously impossible!Tim O'Reilly
My keynote at SxSW Interactive on March 9, 2018. I tackle the job of the entrepreneur to redraw the map, and not to accept the idea that technology will put people out of work rather than creating new kinds of prosperity. I try to provide a call to action to throw off the shackles of the old world and to build a new one. So many companies play defense. Cut costs, watch the competition, follow best practices. Great entrepreneurs like Jeff Bezos and Elon Musk play offense. They see the world with fresh eyes, taking off the blinders that keep companies using technology to make slight improvements to existing products and practices, rather than imagining the world as it could be, given the new capabilities that technology has given us.
My talk to the joint OECD/G20 German Presidency conference on digitalization in Berlin on January 12, 2017. Fitness landscapes as applied to technology, business, and the economy. Note that the fitness landscape slides will not be animated in this PDF, which I shared this way so that you could see my narrative in the speaker notes. While it has some slides in common with my White House Frontiers conference talk, it includes a bunch of other material.
My keynote at the 2018 New Profit Gathering of Leaders conference in Boston on May 17, 2018. I talk about the lessons from technology platforms, how they teach us what is wrong with our economy, and the possibilities of AI for creating better, fairer, more effective decisions about "who gets what and why" in the economy.
My talk at the White House Frontiers Conference at CMU on October 13, 2016. I was one of the warmup acts for the President, talking about why we should embrace an AI future. Full text can be seen here
My keynote at the Open Exchange Summit in Nashville on April 18, 2018. I talk about the implications for many different kinds of companies of the fact that increasingly large segments of our economy are being dominated by algorithmically managed network marketplaces.
My keynote at OSCON 2018 in Portland. What I love about open source software, and what that teaches us about how we can have a better future by the better design of online marketplaces and the algorithms that manage them - and our entire economy. The narrative is in the speaker notes.
What's Wrong With Silicon Valley's Growth ModelTim O'Reilly
A talk I gave on the oreilly.com live training platform on January 22, 2020, focusing on the way that many Silicon Valley startups are designed to be financial instruments rather than real companies. They are gaming the financial system, much like the CDOs that fueled the 2009 financial crash. I talk about the rise of profitless IPOs, and contrast that with the huge profits of the last wave of Silicon Valley giants. In many ways, it is an extended meditation on Benjamin Graham's famous statement, "In the short term, the market is a voting machine, but in the long term it is a weighing machine."
No jobs for humans: How to survive and thrive the transition to the all robot...AJ Davis
Many experts believed driving was too complex to be automated, yet here we are with self driving taxis, cars, and trucks. The robots are coming for drivers - and they are coming for you too. No matter what your job, a robot WILL do it. They will be stronger, faster, and smarter than you. They will be better writers, better doctors, and run companies more effectively.
We can delay the inevitable by shutting down borders and subsidizing losing industries, but we will not stop robots from replacing human labor (nor should we). The challenge is in the transition from a human labor to the robot run economy. Many people will struggle to find new places for their skills, and the result could be increased income inequality, increased violence, and an uprooted sense of self.
In this talk, we’ll explore our responsibility as technologists to be aware of and address this inevitable transition to a robot labor force.
A brochure-style presentation to introduce the big picture vision for R7 Partners, a venture capital firm that finds, funds, and builds early-stage startups with ambitious innovation.
AI and its allied technolgies present an exciting scenario of job changes in coming decades. So are the concerns about loss of traditional jobs. What would be the net impact? We explore the economic models and concepts that allay unfound fears; yet warn us to be ready for constant changes and need for continuous skill rebuilding.
Five Disruptive Technologies and Their Impact on Connecticut's JobsBillKelvie
Technology disruption will cause the loss of 47% of jobs according to a recent Oxford study. This research looks at five technologies which will drive this wrenching change: Artificial Intelligence, Autonomous Vehicles, Electronic Commerce, Internet of Things and Robotics. It examines the impact on CT but is very applicable to the United States as well.
WTF - Why the Future Is Up to Us - pptx versionTim O'Reilly
This is the talk I gave January 12, 2017 at the G20/OECD Conference on the Digital Future in Berlin. I talk about fitness landscapes as applied to technology and business, the role of unchecked financialization in the state of our politics and economy, and why technology really wants to create jobs, not destroy them. (There is a separate PDF version, but some readers said the notes were too fuzzy to read.)
The AIs Are Not Taking Our Jobs...They Are Changing ThemTim O'Reilly
My talk at the Web Summit in Dublin on November 6, 2014. Reflections on the notion that AI will take away jobs, and our need to recognize and redefine the human role in the applications we build. Covers many of the same ideas as my "Internet of Things and Humans" talk, but from a slightly different angle.
But, as Musk’s above-quoted statement suggests, the rise of AI has so far occurred in a regulatory vacuum. With the exception of a few states’ passage of legislation regarding autonomous vehicles and drones, very few laws or regulations exist that specifically address the unique challenges raised by artificial intelligence, and virtually no courts appear to have developed standards specifically addressing who should But, as Musk’s above-quoted statement suggests, the rise of AI has so far occurred in a regulatory vacuum. With the exception of a few states’ passage of legislation regarding autonomous vehicles and drones, very few laws or regulations exist that specifically
address the unique challenges raised by artificial intelligence, and virtually no courts appear to have developed standards specifically addressing who should be held legally responsible if an AI causes harm.
Principles of Artificial Intelligence & Machine LearningJerry Lu
Artificial intelligence has captivated me since I worked on projects at Google that ranged from detecting fraud on Google Cloud to predicting subscriber retention on YouTube Red. Looking to broaden my professional experience, I then entered the world of venture capital by joining Baidu Ventures as its first summer investment associate where I got to work with amazingly talented founders building AI-focused startups.
Now at the Wharton School at the University of Pennsylvania, I am looking for opportunities to meet people with interesting AI-related ideas and learn about the newest innovations within the AI ecosystem. Within the first two months of business school, I connected with Nicholas Lind, a second-year Wharton MBA student who interned at IBM Watson as a data scientist. Immediately recognizing our common passion for AI, we produced a lunch-and-learn about AI and machine learning (ML) for our fellow classmates.
Using the following deck, we sought to:
- define artificial intelligence and describe its applications in business
- decode buzzwords such as “deep learning” and “cognitive computing”
- highlight analytical techniques and best practices used in AI / ML
- ultimately, educate future AI leaders
The lunch-and-learn was well received. When it became apparent that it was the topic at hand and not so much the free pizzas that attracted the overflowing audience, I was amazed at the level of interest. It was reassuring to hear that classmates were interested in learning more about the technology and its practical applications in solving everyday business challenges. Nick and I are now laying a foundation to make these workshops an ongoing effort so that more people across the various schools of engineering, design, and Penn at large can benefit.
With its focus on quantitative rigor, Wharton already feels like a perfect fit for me. In the next two years, I look forward to engaging with like-minded people, both in and out of the classroom, sharing my knowledge about AI with my peers, and learning from them in turn. By working together to expand Penn’s reach and reputation with respect to this new frontier, I’m confident that we can all grow into next-generation leaders who help drive companies forward in an era of artificial intelligence.
I’d love to hear what you think. If you found this post or the deck useful, please recommend them to your friends and colleagues!
Machine Learning: Understanding the Invisible Force Changing Our WorldKen Tabor
Readers will gain an appreciation for machine learning, and take away valuable strategies including:
• What is machine learning.
• How it’s changing the world.
• Who the major players are.
• How you can control it.
Machine learning. It’s in the news. It’s discussed in corporate boardrooms. It’s on your mind. ML algorithms seem to be at once everywhere, yet nowhere. Can we possibly understand how this invisible force is shaping our world? How will it reform your industry, and change your job?
The State of Artificial Intelligence and What It Means for the PhilippinesThinking Machines
What consumer-ready applications of artificial intelligence are out there? What are the implications of semi-autonomous agents on Manila's BPO industry? Thinking Machines CEO and data scientist Stephanie Sy delivered this presentation on the current data science and AI landscape at the "Humans + Machines: Using Artificial Intelligence to Power Your People" conference held on February 19, 2016 at BGC, Taguig, Philippines.
Humanity will change more in the next 20 years than in the previous 300 years. What if …robots replaced the world’s workforce?
This is the presentation delivered by Glen Leonhard at London Business School's 2015 Global Leadership Summit.
Technology is completely changing the face of financial services, driving disruption, displacement and disintermediation within the sector. This has lowered the barriers to entry, opened the door to new market entrants and created fertile ground for innovation and growth.
These market disruptions have also forged new alliances between start-ups and incumbents, blurring the lines of distinction between finance and technology and creating a wave of cross-sector collaboration.
Fintech 2018 will explore technological innovation across the financial services sector, from developments in established tier-1 firms to the disruptive innovators within the start-up community that are reshaping the FS market.
Core conference topics will include:
• Landscape: Trends, Culture, Trust, Transparency, Geo-political Climate
• Regulation: GDPR, MiFID II, PSD2, Open Banking, APIs
• Customer Strategy: Engagement, UX, Data Insight, Marketing & ML
• Emerging Tech: Blockchain, Analytics, AI, Payments, Automation
• National Strategy: Skills, Funding, Collaboration, Cyber Security
• Infrastructure: IT, Digital, Cloud, Mobile, XaaS
AI IS EATING THE WORLD
Since the industrial revolution we have seen that we automate every system the can be automated efficiently. Created massive distribution of wealth.
With AI and Bots, we are moving from automating “simple” repetitive tasks to autonomous systems that can handle complex and changing situations. It is not a question what verticals will be disrupted, it is a question of when, a few examples…
Maritime Information Warfare - The Human DimensionAndy Fawkes
Presented at SMi's Inaugural Maritime Information Warfare Conference, London, 6/7 December 2017. A perspective on the modern sailor, training and simulation, training data, and defence organisational challenges.
A somewhat longer version of my Frontiers talk about technology and the future of the economy, with additional material pitched to an audience of Internet operators at Apricot 2017, in Ho Chi Minh City, Vietnam on February 27, 2017
AI and the Future of Work - Cloud Wars Expo 2022 - Dan Turchin - PeopleReign.pdfPeopleReign, Inc.
Work has changed more in the past 30 months than in the previous 30 years. We’re realizing it’s ok to love what we do. It’s ok to expect leaders to respect our time and our values. It’s ok to want to do the best work of our lives.
We’ll look back on this period as one when we were on the cusp of developing a new relationship with thinking machines. It will seem quaint that there was a time when humans did work better suited for machines and machines did work better suited for humans. We’ll soon reconcile our complicated relationship with technology and embrace digital labor. Many careers won’t survive the transition but far more will be created. The workplace won’t resemble today’s office but we’ll be more productive and happier.
Attend this to session to learn:
The optimal way to distribute work across geographies, languages, and physical spaces
How to prepare for a future where decisions are made by combining input from carbon and silicon-based brains
Why more technology will make it easier to be better humans
Be prepared to question everything you thought you knew about the future of work. Join us for 25 minutes that just may change your life.
"AI is “our greatest existential threat…”
“I’m increasingly inclined to think that there should be some regulatory oversight, maybe at the national and international level, just to make sure that we don’t do something very foolish.”
“I think there is potentially a dangerous outcome there.” (referring to Google’s Deep Mind which he invested in to keep an eye on things)."
Elon Musk
AI and the future workforce - People disruption or opportunity?Simone Edwards
As part of London Tech Week, Dr Charlotte Werger from ASI Data Science and Dr Tim Sparkes from Hudson explore the future of AI in business, the impact it will have over jobs and the opportunities it presents for businesses.
Similar to Redesigning work in an age of automation (20)
Global food trends: How are countries embracing the alternative protein movementPlan
Our relationship with food is at a tipping point as environmental concerns become more of a consumer focus. What is the appetite, globally, for a more sustainable plant-based diet and how do cultural differences impact the adoption of innovative flexitarian products?
A revised view on the future of Mobility – rowing back from the heady daze of 2017. Using the CASE (Connected, Autonomous, Shared and Electric) framework, we contrast the optimism of a view years ago, with the more grounded view of today.
The mobility disruption around the corner will largely initiated by three technology advances, but the knock-on impacts will be shaped by economic and social choices, as much as technology.
A 10min presentation on some foreseen – and less foreseen – consequences of Autonomous Vehicles, I gave at the #CarTubeGlobal launch event at Institution of Mechanical Engineering today
Introduction and mobility survey slides from the Plan Forum on the Future of Urban Mobility, in partnership with Bloomberg New Energy Finance.
London, 15th March 2016
A challenging review of the future of user interfaces, and a plea to better focus and shun the shiny:
– triangulate through experts
– observe emergent behaviour
– and track a range of trends.
Get out the echochamber and avoid the human centipede of digital rhetoric. Listen harder with your eyes and critique better with your mind.
Bridging the Physical-Digital Divide: Industrial Designer EditionPlan
With the proliferation of touchscreens and a hardware revival driven by internet technologists, Industrial Design is at risk of becoming irrelevant.
How can Industrial Design engage with the technology, user experience and software communities to help create harmony across physical products and digital services?
From research with 30+ Industrial Designers, User Experience designers and technologists, I concluded that the divide can be broken down across a series of axes and bridged by connecting, calibrating and collaborating.
A cut-down Industrial Designer oriented version of a longer 45 minute presentation for Interactions 14.
Plans Head of UX, Jason Mesut has also been doing his bit to quell the UX talent drought. His talk to UX newbies at General Assembly on what employers are looking for, has also been a hit online (view on Slideshare). On top of this, Jason has been working with some other leaders in the field to develop a course on digital Experience Design for Hyper Island.
Alex Bradley, Plan’s head of trends, recently gave a trends presentation at the TAID conference in Taiwan.
The following slides give a taste of the presentation. Please contact Alex at alex@plan.bz if you’re interested in him sharing it with your team?
Kevin's closing keynote presentation at the Design Management Institute's conference in London in 2010.
The presentation tackled two key questions: Why is design thinking such a hot topic with executives, but leaves so many designers cold? And: Does the demand for design thinking represent more of an opportunity than the thinking itself?
It was based on an article of the same title for the Design Management Review http://www.plan.bz/plan-views/2010/september/steppingup
In a future where digital services and physical products come together, it seems like the tech community is having the greatest influence on our world. In some ways, this is great, but we seem to have forgotten those designers with the talent for crafting physical forms that can fit into our hands, our homes and our lives.
For a future Internet of Things, the UX community needs to better engage Industrial Designers in what we do. This talk explored how we do that.
NB, this is a talk intended for a UX audience, and is meant to be a starter of an ongoing discussion between both UX and Industrial Design fields. If you want to be part of the discussion, please get in contact.
Attending a job Interview for B1 and B2 Englsih learnersErika906060
It is a sample of an interview for a business english class for pre-intermediate and intermediate english students with emphasis on the speking ability.
Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
Digital Transformation and IT Strategy Toolkit and TemplatesAurelien Domont, MBA
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
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Redesigning work in an age of automation
1. Redesigning work in
an age of automation
Kevin McCullagh
Leaders of Change
05 December 2018
2.
3. ‘There certainly will be job
disruption. Because what’s
going to happen is robots
will be able to do everything
better than us. ... I mean
all of us’.
Elon Musk, National Governors Association, 16 July 2017
7. ‘Consider thou what the
invention could do to my
poor subjects. It would
assuredly bring them to
ruin by depriving them of
employment, thus making
them beggars’
Elizabeth I, on refusing to patent a knitting
machine invented by William Lee
9. There many
reasons to be
cheerful about
Automation
Most jobs are
best tackled with
a mix of human
and machine
strengths
1 2
10. There many
reasons to be
cheerful about
Automation
Most jobs are
best tackled with
a mix of human
and machine
strengths
Most jobs will
be redesigned to
take advantage
of automation...
1 2 3
11. There many
reasons to be
cheerful about
Automation
Most jobs are
best tackled with
a mix of human
and machine
strengths
Most jobs will
be redesigned to
take advantage
of automation...
including design
1 2 3
14. Automation Productivity Prosperity
GDP per capita in England since 1270
Adjusted for inflation and measured in British Pounds in 2013 prices (000s)
1270 1400 1500 1600 1700 1800 1900 2016
Source: GDP in England (using BoE 2017), OurWorldInData.org/economic-growth
30
25
20
15
10
5
0
16. Dismally low productivity growth
-2%
0%
2%
4%
6%
8% World
War I
World
War II
Great
Depression
Great
Recession
McKinsey Global Institute: Solving the productivity puzzle; Brookings Institution
United States
Europe
Great
Recession
Annual productivity growth
1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2018
27. Bank tellers vs. ATM machines
Fulltime-equivalent bank tellers
and installed ATM machines in the US
Tellers/ATMs(1000s)
500
400
300
200
100
0
1970 1980 1990 2000 2010
Source: James Bessen, How computer automation affects occupations:
Technology, jobs, and skills’, 22 September 2016, Vox
ATMs
28. Bank tellers vs. ATM machines
Fulltime-equivalent bank tellers
and installed ATM machines in the US
Tellers/ATMs(1000s)
500
400
300
200
100
0
1970 1980 1990 2000 2010
Source: James Bessen, How computer automation affects occupations:
Technology, jobs, and skills’, 22 September 2016, Vox
Fulltime
equivalent
workers
ATMs
32. New technology generally
reshapes jobs, rather than
replaces them. It takes
on the mundane tasks,
as humans tend to move
onto more complex – and
often more meaningful –
work.
36. ‘Machines are good
for repetitive things,
but they can’t
improve their own
efficiency or the
quality of their work.
Only people can.’
President of Toyota Manufacturing Plant,
Kentucky
48. [I aim to make]
‘machines
slightly more
intelligent —
or slightly
less dumb.’
John Giannandrea, Head of AI, Apple
49. ‘The real danger ... is not
machines that are more
intelligent than we are ...
The real danger is basically
clueless machines being
ceded authority far beyond
their competence.’
Daniel Dennett, ‘The Singularity—an
Urban Legend’, Edge
52. ‘[people] will set the goals,
formulate the hypotheses,
determine the criteria, and
perform the evaluations.
53. ‘Men will set the goals, formulate
the hypotheses, determine
the criteria, and perform the
evaluations.
‘Computing machines will do
the routinizable work that must
be done to prepare the way for
insights and decisions. . .
54. ‘The symbiotic partnership will
perform intellectual operations
much more effectively than man
alone can perform them…’
J. C. R. Licklider, ‘Man-computer symbiosis,’ 1960
64. Assigned
– Certain tasks in a
human workflow
are outsourced
to a machine.
– The machine
completes
the task unaided,
with varying
levels
of instruction.
66. Supervised
– Decision making
processes are
automated, but
under a human
eye.
– This mode
requires the
machine to be
aware
of and
communicate
risks and
unknowns
to human users.
68. Coexistent
– We will
increasingly
live and work
alongside
intelligent
machines,
sharing the
same spaces,
but focusing on
separate task-
flows.
– Machines in
these scenarios
must be able
to effectively
negotiate shared
space and
anticipate human
intent.
70. Source: Jaguar Land Rover Bike Sense. Seat shoulder taps the rings a bicycle bell if it senses a cyclist near the car
and Door handles ‘buzz’ to prevent doors being opened into the path of bikes
Assistive
– Machines that
will help
us perform tasks
faster
and better.
– They support
particular
tasks in human
workflows, and
will excel in
discerning
human goals
and learning their
preferences.
72. Symbiotic
– This emerging
mode of
collaboration is a
highly interactive
and reciprocal.
– People input
strategic
hypotheses and
the machine
suggests tactical
options.
79. Facilitating automation
Training
Teaching
machines how
to perform
tasks or act
more human
Job titles
– Automation design
anthropologist
– Data hygienist
– Empathy trainer
– Personality trainer
– Worldview trainer
– Interaction modeller
Activities
– Identifying relevant
data
– Cleaning data
– Tagging data
– Having machine
observe decision
making
– Improving machine
language
– Defining and
developing brand
AI personalityMellisa Cefkin, AV design anthropologist, Nissan
84. Human augmentation
Interacting
AI agents with
advanced
voice-driven
interfaces
facilitate
interactions
between
people at
scale
Activities
– Answer customer
support FAQs,
and hand-on hard
questions to humans
– Accelerate customer
understanding based
on context
– Enable natural
language querying
SEB Aida chatbot
85. Human augmentation
Embodying
AI combines
with
sensors and
actuators to
allow robots
to safely and
effectively
physically
augment
human
workers
Activities
– Navigate around
humans
– Extend sight,
hearing and
touch
– Assist with
precise, repetitive
and physically
arduous work
Cobots at BMW
88. Design and tech careers are
forecast to be among the winners
McKinsey, 2018
Skills
Hours worked in
2016 (billions)
Change in hours
worked by 2030 (%)
Change in hours
worked by 2030 (%)
Hours worked in
2016 (billions)
Physical and manual
Basic cognitive
Higher cognitive
Social and emotional
Technological
90
53
62
52
31
113
62
78
67
90
-11 -16
-14 -17
+09 +07
+26 +22
+60 +52
92. Redesigning design
with AI
Level of sophistication
2Empathise
AI uncovers new insights
from existing consumer or
user insight data
7Optimise
AI optimises parameters
1Discover
AI identifies new data
patterns and connections
6Test
AI lowers the analysis load
3Generate
AI created design options
within predefined constraints
8Customise
AI enables new levels of
personalisation
4Prototype
AI accelerates and
democratises prototyping
9Collaborate
AI facilitates more effective
collaboration
5Refine
AI accelerates iteration
and unlocks new creative
possibilities
10Hire
AI streamlines hiring process