Global Governance of Generative AI: The Right Way ForwardLilian Edwards
AI regulation has been a hot topic since the rise of machine learning (ML) in the “big data” era, but generative AI or “foundation models” tools like ChatGPT, DALL-E 2(now 3) and CoPilot, ike ML before them, may create serious societal risks, including embedding and outputting bias; generating fake news, illegal or harmful content and inadvertent “hallucinations”; infringing existing laws relating eg to copyright and privacy; as well as environmental, competition and workplace concerns.
Many nations are now considering regulation to address these worries, and can draw on a number of basic and hybrid models of governance. This paper canvasses models of mandatory comprehensive legislation (where the EU AI Act hopes to place itself as a gold standard model); vertical mandatory legislation (where China has quietly taken a lead); adapting existing law (see the many copyright lawsuits underway); and voluntary “soft law” such as codes of ethics, “blueprints”, or industry guidelines. Both the domestic and international regulatory scenes for AI are also increasingly politicised as the rise of "AI safety" hype shows. Against this backdrop what choices should smaller countries such as the UK and Australia make? will international harmonisation lead to a race to the top as with the GDPR, or the bottom - rule by tech for tech?
The Revolution of Digital Marketing in the Artificial Intelligence eraMohamed Hanafy
In this course, we will explore the impact of artificial intelligence on the field of digital marketing. We will discuss how AI technologies such as machine learning, natural language processing, and predictive analytics are revolutionizing the way businesses approach marketing. We will also examine real-world examples of how companies are using AI to improve their marketing strategies and achieve better results.
Smart City Lecture 2 - Privacy in the Smart CityPeter Waher
Privacy is a basic human right that has been heavily eroded on the point of extinction in the current digital age, as the constant reports on security breaches tell us. With the help of the General Data Protection Regulation (GDPR), privacy has been brought back from the dead, and is at least discussed in most enterprises in Europe, and perhaps a large part of the world. This lecture introduces the GDPR and Privacy, as it relates to the Smart City. It presents concepts such as “Data Protection by design and by default”, “Consent”, “Legal Basis”, etc. It also presents technologies that make protecting Privacy more difficult, and why.
These technologies work against the basic principles of privacy by default, so you need to know the details of how they work, to avoid serious pitfalls. There are also technologies that are more Privacy neutral. While not making data protection easier, at least the technology does not work against the basic principles of privacy. Finally, technologies that intrinsically help you protect Privacy are presented. These technologies make it easier to protect Privacy and sensitive data in general.
Executive Perspective Building an OT Security Program from the Top Downaccenture
Designed for executives, this non-technical track addresses key components of a successful OT security program. The discussions are intended to spark conversation and this guide highlights key takeaways on what works, what doesn’t and what’s next. https://accntu.re/3N7KmiZ
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI has dominated the headlines recently, which has caused many enterprises to put a full stop to implementing this technology until they can understand what’s behind the glitz and glamour. What if we shifted the conversation? What if the focus became a fresh, incremental approach to embracing the opportunities with generative artificial intelligence to keep organizations moving upward on the S Curve of Growth?
Brands stay relevant and solve complex problems by testing the barometer for one thing — will a new strategy, tool, or piece of technology improve humanity?
Human connections are more vital than using shiny new tools or technology. As your teams work to steer clear of the temptation to do what everyone else is doing in uniform, this post will highlight how to stand out, compete, and do so with less risk in today’s world of generative AI overload.
Global Governance of Generative AI: The Right Way ForwardLilian Edwards
AI regulation has been a hot topic since the rise of machine learning (ML) in the “big data” era, but generative AI or “foundation models” tools like ChatGPT, DALL-E 2(now 3) and CoPilot, ike ML before them, may create serious societal risks, including embedding and outputting bias; generating fake news, illegal or harmful content and inadvertent “hallucinations”; infringing existing laws relating eg to copyright and privacy; as well as environmental, competition and workplace concerns.
Many nations are now considering regulation to address these worries, and can draw on a number of basic and hybrid models of governance. This paper canvasses models of mandatory comprehensive legislation (where the EU AI Act hopes to place itself as a gold standard model); vertical mandatory legislation (where China has quietly taken a lead); adapting existing law (see the many copyright lawsuits underway); and voluntary “soft law” such as codes of ethics, “blueprints”, or industry guidelines. Both the domestic and international regulatory scenes for AI are also increasingly politicised as the rise of "AI safety" hype shows. Against this backdrop what choices should smaller countries such as the UK and Australia make? will international harmonisation lead to a race to the top as with the GDPR, or the bottom - rule by tech for tech?
The Revolution of Digital Marketing in the Artificial Intelligence eraMohamed Hanafy
In this course, we will explore the impact of artificial intelligence on the field of digital marketing. We will discuss how AI technologies such as machine learning, natural language processing, and predictive analytics are revolutionizing the way businesses approach marketing. We will also examine real-world examples of how companies are using AI to improve their marketing strategies and achieve better results.
Smart City Lecture 2 - Privacy in the Smart CityPeter Waher
Privacy is a basic human right that has been heavily eroded on the point of extinction in the current digital age, as the constant reports on security breaches tell us. With the help of the General Data Protection Regulation (GDPR), privacy has been brought back from the dead, and is at least discussed in most enterprises in Europe, and perhaps a large part of the world. This lecture introduces the GDPR and Privacy, as it relates to the Smart City. It presents concepts such as “Data Protection by design and by default”, “Consent”, “Legal Basis”, etc. It also presents technologies that make protecting Privacy more difficult, and why.
These technologies work against the basic principles of privacy by default, so you need to know the details of how they work, to avoid serious pitfalls. There are also technologies that are more Privacy neutral. While not making data protection easier, at least the technology does not work against the basic principles of privacy. Finally, technologies that intrinsically help you protect Privacy are presented. These technologies make it easier to protect Privacy and sensitive data in general.
Executive Perspective Building an OT Security Program from the Top Downaccenture
Designed for executives, this non-technical track addresses key components of a successful OT security program. The discussions are intended to spark conversation and this guide highlights key takeaways on what works, what doesn’t and what’s next. https://accntu.re/3N7KmiZ
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI has dominated the headlines recently, which has caused many enterprises to put a full stop to implementing this technology until they can understand what’s behind the glitz and glamour. What if we shifted the conversation? What if the focus became a fresh, incremental approach to embracing the opportunities with generative artificial intelligence to keep organizations moving upward on the S Curve of Growth?
Brands stay relevant and solve complex problems by testing the barometer for one thing — will a new strategy, tool, or piece of technology improve humanity?
Human connections are more vital than using shiny new tools or technology. As your teams work to steer clear of the temptation to do what everyone else is doing in uniform, this post will highlight how to stand out, compete, and do so with less risk in today’s world of generative AI overload.
Energy IIoT - Industrial Internet of Things (IIoT) in Decentralized Digital O...crlima10
This presentation introduces the framework for an Industrial Internet of Things (IIoT) convergence towards edge/fog computing. It also defines new industry concepts of "Decentralized Digital Oilfield -DDOF" with semi-autonomous intelligent IIoT operation technology (OT), enabled by Blockchain.
Privacy in AI/ML Systems: Practical Challenges and Lessons LearnedKrishnaram Kenthapadi
How do we protect the privacy of users when building large-scale AI based systems? How do we develop machine learning models and systems taking fairness, accuracy, explainability, and transparency into account? Model fairness and explainability and protection of user privacy are considered prerequisites for building trust and adoption of AI systems in high stakes domains. We will first motivate the need for adopting a “fairness, explainability, and privacy by design” approach when developing AI/ML models and systems for different consumer and enterprise applications from the societal, regulatory, customer, end-user, and model developer perspectives. We will then focus on the application of privacy-preserving AI techniques in practice through industry case studies. We will discuss the sociotechnical dimensions and practical challenges, and conclude with the key takeaways and open challenges.
To assess the current state of digital process automation within the federal government, Accenture engaged Market Connections to survey 200 federal government executives across both defense and civilian agencies. The survey was fielded in February-March 2018. These were program leaders with mission, business or operational responsibilities for business processes and service delivery within their agency. Read more https://accntu.re/2D9Kj3B
Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic...DATAVERSITY
The Digital Economy is changing the way organizations do business across the globe, and is set to transform the economy on an unprecedented scale. Business optimization, and entirely new business models are emerging as data-driven technology provides unprecedented opportunity for innovation and change. In many organizations, data not only supports business profitability, but data itself has become the critical business asset.
What does it mean to leverage data as a business asset? And how can today’s data-centric technologies support the data-driven revolution? Join our expert panelists as they discuss the latest innovations in the data landscape.
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
leewayhertz.com-The architecture of Generative AI for enterprises.pdfKristiLBurns
Generative AI is quickly becoming popular among enterprises, with various applications being developed that can change how businesses operate. From code generation to product design and engineering, generative AI impacts a range of enterprise applications.
Impact of Artificial Intelligence/Machine Learning on Workforce CapabilityLearningCafe
The application of AI/ML is reshaping the job market and will eventually create new jobs & roles that we can’t even imagine today. Reskilling the workforce and reforming learning and career models will play a critical role in facilitating this change. The question remains if that will be provided by the traditional internal HR/L&D team or some other model.
“AI is the new electricity” proclaims Andrew Ng, co-founder of Google Brain. Just as we need to know how to safely harness electricity, we also need to know how to securely employ AI to power our businesses. In some scenarios, the security of AI systems can impact human safety. On the flip side, AI can also be misused by cyber-adversaries and so we need to understand how to counter them.
This talk will provide food for thought in 3 areas:
Security of AI systems
Use of AI in cybersecurity
Malicious use of AI
Digital Transformation in Higher Education - The Changing Student RelationshipAndy Steer
Slide Deck delivered at SAP's Digital Transformation for Public Services event.
If you think that SAP and higher education is just about finance and HR then think again.
As SAP’s chosen Global Partner for higher education, itelligence are focused on bringing real innovation to your sector. From back office systems that save you time and money to consumer grade engagement platforms that drive student and staff recruitment, retention, and performance through to big data and analytic solutions that deliver actionable insight early to promote positive outcomes.
Bringing the best in SAP Consulting know-how and a range of services from implementation, training, support, and hosting, itelligence is the partner for tomorrow’s higher education institution.
Generative AI in Transportation for Connected Future Transport System July 20...Sudha Jamthe
Sudha Jamthe keynote about Generative AI in smart mobility in the future of transportation
Follow Sudha Jamthe at sudhajamthe.com or learn more about Generative AI at generativeaibook.org
This slide shows (1) AI and Accountability , (2) AI Ethics, (2) Privacy Protection. Several AI ethics documents such as IEEE EAD, EC-HELG Ethics Guideline for Trustworthy AI, Social Principles of Human-Centric AI(Japan), focus on AI's transparency, accountability and trust. We follow the discussions of these documents around the above (1),(2) and (3) topics.
This webinar covers:
- An overview of the regulatory landscape and territorial scope
- Principles of the EU GDPR
- Breach notification rules
- Data subject rights
- Changes to consent
- Processor liabilities
- Role of the Data Protection Officer
A recording of this webinar is available here: https://www.youtube.com/watch?v=bEvXj2nhPd0
Developing & Deploying Effective Data Governance FrameworkKannan Subbiah
This is the slide deck presented at the Customer Privacy and Data Protection India Summit 2019 held in Mumbai, India. The specific topics touched upon are the guiding principles, Aligning with Data Architecture, Data Quality & Compliance.
Chat GPT 4 can pass the American state bar exam, but before you go expecting to see robot lawyers taking over the courtroom, hold your horses cowboys – we're not quite there yet. That being said, AI is becoming increasingly more human-like, and as a VC we need to start thinking about how this new wave of technology is going to affect the way we build and run businesses. What do we need to do differently? How can we make sure that our investment strategies are reflecting these changes? It's a brave new world out there, and we’ve got to keep the big picture in mind!
Sharing here with you what we at Cavalry Ventures found out during our Generative AI deep dive.
After analysing the key AI technologies that can be applied in the public sector, the course gives an overview of potential applications (e.g. chatbots, intelligent agents, decision making algorithms, machine learning systems, etc) in various European countries and sectors of the economy. Furthermore, the aims, the benefits and the possible challenges and risks of such applications are being presented, together with the means for risk mitigation. The course also presents the main initiatives for promoting , monitoring and regulating the use of artificial intelligence in the public sector, in Europe and the world.
Artificial intelligence governance in the Obama & Trump yearsAdam Thierer
This presentation briefly outlines how AI governance was being formulated in the United States from 2009 to 2020 during the presidencies of Barack Obama and Donald Trump. Although these two administrations differed on most policy matters, they shared a common approach to AI governance. Generally speaking, both administrations adopted a “light-touch” regulatory and industrial policy stance toward AI. Although both administrations highlighted potential areas of policy concern—safety and security issues, in particular—promoting the growth of AI sectors and technologies was prioritized over preemptively restricting them. “Soft law” mechanisms were typically tapped before hard law solutions. In this sense, AI policy in the Obama-Trump AI governance approach has been an extension of the governance vision previous administrations applied to the internet and digital commerce.
“Permissionless Innovation” & the Grand Tech Policy Clash of Visions to ComeMercatus Center
Successful innovation, which is essential to better health, safety and security, requires freedom to experiment and develop. But there is an array of government rules and processes that increasingly prohibit “permissionless” innovation.
Energy IIoT - Industrial Internet of Things (IIoT) in Decentralized Digital O...crlima10
This presentation introduces the framework for an Industrial Internet of Things (IIoT) convergence towards edge/fog computing. It also defines new industry concepts of "Decentralized Digital Oilfield -DDOF" with semi-autonomous intelligent IIoT operation technology (OT), enabled by Blockchain.
Privacy in AI/ML Systems: Practical Challenges and Lessons LearnedKrishnaram Kenthapadi
How do we protect the privacy of users when building large-scale AI based systems? How do we develop machine learning models and systems taking fairness, accuracy, explainability, and transparency into account? Model fairness and explainability and protection of user privacy are considered prerequisites for building trust and adoption of AI systems in high stakes domains. We will first motivate the need for adopting a “fairness, explainability, and privacy by design” approach when developing AI/ML models and systems for different consumer and enterprise applications from the societal, regulatory, customer, end-user, and model developer perspectives. We will then focus on the application of privacy-preserving AI techniques in practice through industry case studies. We will discuss the sociotechnical dimensions and practical challenges, and conclude with the key takeaways and open challenges.
To assess the current state of digital process automation within the federal government, Accenture engaged Market Connections to survey 200 federal government executives across both defense and civilian agencies. The survey was fielded in February-March 2018. These were program leaders with mission, business or operational responsibilities for business processes and service delivery within their agency. Read more https://accntu.re/2D9Kj3B
Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic...DATAVERSITY
The Digital Economy is changing the way organizations do business across the globe, and is set to transform the economy on an unprecedented scale. Business optimization, and entirely new business models are emerging as data-driven technology provides unprecedented opportunity for innovation and change. In many organizations, data not only supports business profitability, but data itself has become the critical business asset.
What does it mean to leverage data as a business asset? And how can today’s data-centric technologies support the data-driven revolution? Join our expert panelists as they discuss the latest innovations in the data landscape.
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
leewayhertz.com-The architecture of Generative AI for enterprises.pdfKristiLBurns
Generative AI is quickly becoming popular among enterprises, with various applications being developed that can change how businesses operate. From code generation to product design and engineering, generative AI impacts a range of enterprise applications.
Impact of Artificial Intelligence/Machine Learning on Workforce CapabilityLearningCafe
The application of AI/ML is reshaping the job market and will eventually create new jobs & roles that we can’t even imagine today. Reskilling the workforce and reforming learning and career models will play a critical role in facilitating this change. The question remains if that will be provided by the traditional internal HR/L&D team or some other model.
“AI is the new electricity” proclaims Andrew Ng, co-founder of Google Brain. Just as we need to know how to safely harness electricity, we also need to know how to securely employ AI to power our businesses. In some scenarios, the security of AI systems can impact human safety. On the flip side, AI can also be misused by cyber-adversaries and so we need to understand how to counter them.
This talk will provide food for thought in 3 areas:
Security of AI systems
Use of AI in cybersecurity
Malicious use of AI
Digital Transformation in Higher Education - The Changing Student RelationshipAndy Steer
Slide Deck delivered at SAP's Digital Transformation for Public Services event.
If you think that SAP and higher education is just about finance and HR then think again.
As SAP’s chosen Global Partner for higher education, itelligence are focused on bringing real innovation to your sector. From back office systems that save you time and money to consumer grade engagement platforms that drive student and staff recruitment, retention, and performance through to big data and analytic solutions that deliver actionable insight early to promote positive outcomes.
Bringing the best in SAP Consulting know-how and a range of services from implementation, training, support, and hosting, itelligence is the partner for tomorrow’s higher education institution.
Generative AI in Transportation for Connected Future Transport System July 20...Sudha Jamthe
Sudha Jamthe keynote about Generative AI in smart mobility in the future of transportation
Follow Sudha Jamthe at sudhajamthe.com or learn more about Generative AI at generativeaibook.org
This slide shows (1) AI and Accountability , (2) AI Ethics, (2) Privacy Protection. Several AI ethics documents such as IEEE EAD, EC-HELG Ethics Guideline for Trustworthy AI, Social Principles of Human-Centric AI(Japan), focus on AI's transparency, accountability and trust. We follow the discussions of these documents around the above (1),(2) and (3) topics.
This webinar covers:
- An overview of the regulatory landscape and territorial scope
- Principles of the EU GDPR
- Breach notification rules
- Data subject rights
- Changes to consent
- Processor liabilities
- Role of the Data Protection Officer
A recording of this webinar is available here: https://www.youtube.com/watch?v=bEvXj2nhPd0
Developing & Deploying Effective Data Governance FrameworkKannan Subbiah
This is the slide deck presented at the Customer Privacy and Data Protection India Summit 2019 held in Mumbai, India. The specific topics touched upon are the guiding principles, Aligning with Data Architecture, Data Quality & Compliance.
Chat GPT 4 can pass the American state bar exam, but before you go expecting to see robot lawyers taking over the courtroom, hold your horses cowboys – we're not quite there yet. That being said, AI is becoming increasingly more human-like, and as a VC we need to start thinking about how this new wave of technology is going to affect the way we build and run businesses. What do we need to do differently? How can we make sure that our investment strategies are reflecting these changes? It's a brave new world out there, and we’ve got to keep the big picture in mind!
Sharing here with you what we at Cavalry Ventures found out during our Generative AI deep dive.
After analysing the key AI technologies that can be applied in the public sector, the course gives an overview of potential applications (e.g. chatbots, intelligent agents, decision making algorithms, machine learning systems, etc) in various European countries and sectors of the economy. Furthermore, the aims, the benefits and the possible challenges and risks of such applications are being presented, together with the means for risk mitigation. The course also presents the main initiatives for promoting , monitoring and regulating the use of artificial intelligence in the public sector, in Europe and the world.
Artificial intelligence governance in the Obama & Trump yearsAdam Thierer
This presentation briefly outlines how AI governance was being formulated in the United States from 2009 to 2020 during the presidencies of Barack Obama and Donald Trump. Although these two administrations differed on most policy matters, they shared a common approach to AI governance. Generally speaking, both administrations adopted a “light-touch” regulatory and industrial policy stance toward AI. Although both administrations highlighted potential areas of policy concern—safety and security issues, in particular—promoting the growth of AI sectors and technologies was prioritized over preemptively restricting them. “Soft law” mechanisms were typically tapped before hard law solutions. In this sense, AI policy in the Obama-Trump AI governance approach has been an extension of the governance vision previous administrations applied to the internet and digital commerce.
“Permissionless Innovation” & the Grand Tech Policy Clash of Visions to ComeMercatus Center
Successful innovation, which is essential to better health, safety and security, requires freedom to experiment and develop. But there is an array of government rules and processes that increasingly prohibit “permissionless” innovation.
“Permissionless Innovation” & the Clash of Visions over Emerging TechnologiesAdam Thierer
"Permissionless Innovation & the Clash of Visions over Emerging Technologies." A presentation created by Adam Thierer (Mercatus Center at George Mason University). It focuses on coming public policy fights over various emerging technologies, such as: driverless cars, the Internet of Things, wearable technology, commercial drones, mobile medical innovations, virtual reality, and more.
This presentation has been updated to reflect most recent version.
The Future of Innovation of Policy - Adam Thierer - Mercatus CenterAdam Thierer
An overview of the future of innovation policy and what governance vision will drive it -- the precautionary principle or permissionless innovation. (By Adam Thierer, Senior Research Fellow, Mercatus Center at George Mason University).
3D Printing and Permissionless Innovation (Adam Thierer March 2016)Adam Thierer
presentation by Adam Thierer of the Mercatus Center at George Mason University. Made at Univ. of Minnesota Law School symposium on "Legal Concerns in 3D Printing" on March 4, 2016.
Presentation by Keita Nishiyama at the OECD Global Conference on Governance Innovation which took place in Paris on 13-14 January 2020. Further information is available at http://www.oecd.org/gov/regulatory-policy/oecd-global-conference-on-governance-innovation.htm.
Brief summary of how the law and legal practice may be affected by the ris of AI and autonomous cars, robots, etc - with a look at what harms or biases may result and how law and the market might try to solve those problems.
An insight in the legal challenges and opportunities of Artificial Intelligence (AI). By Matthias Dobbelaere-Welvaert, managing partner of theJurists Europe.
How Can Policymakers and Regulators Better Engage the Internet of Things? Mercatus Center
The world today is seemingly always plugged into the Internet and technologies are constantly sharing data about our personal and professional lives. Device connectivity is on an upward trend with Cisco estimating that 50 billion devices will be connected to the Internet by 2020. Collection and data sharing by these devices introduces a host of new vulnerabilities, raising concerns about safety, security, and privacy for policymakers and regulators.
Internet of Things & Wearable Technology: Unlocking the Next Wave of Data-Dri...Adam Thierer
"Internet of Things & Wearable Technology: Unlocking the Next Wave of Data-Driven Innovation." A presentation by Adam Thierer (Mercatus Center at George Mason University) made on September 11, 2014 at AEI-FCC Conference on "Regulating the Evolving Broadband Ecosystem."
Technological innovation is reshaping markets and creating new opportunities for businesses at a faster rate than at any other time in living memory. But to realise the promise of greater economic growth, incumbent businesses, challengers and the policymakers who regulate them need to find a balance that encourages fairness without either stifling entrepreneurialism or compromising the public interest.
Finding this balance has proven difficult for businesses and industry regulators alike.
In order to build greater understanding of the trade-offs at play in ensuring a level playing field, this report explores the specific challenges that regulators face when it comes to disruptors, and explores workable models for increased collaboration between the public and private sectors.
Cyber Libertarianism - Real Internet Freedom (Thierer & Szoka)Adam Thierer
Adam Thierer & Berin Szoka of The Progress & Freedom Foundation are attempting to articulate the core principles of cyber-libertarianism to provide the public and policymakers with a better understanding of this alternative vision for ordering the affairs of cyberspace. We invite comments and suggestions regarding how we should refine and build-out this outline. We hope this outline serves as the foundation of a book we eventually want to pen defending what we regard as “Real Internet Freedom.”
The future of regulation: Principles for regulating emerging technologiesDeloitte United States
As emerging technologies drive new business and service models, governments must rapidly create, modify, and enforce regulations. The preeminent issue is how to protect citizens and ensure fair markets while letting innovation and businesses flourish. https://deloi.tt/2NaeMRD
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
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AI and Robotics policy overview - Adam Thierer (Aug 2022)
1. AI & ROBOTICS
GOVERNANCE: THE POLICY
CHALLENGES AHEAD
ADAM THIERER
SENIOR RESEARCH FELLOW, MERCATUS CENTER AT GEORGE MASON
UNIVERSITY
LAST UPDATED: AUGUST 2022
3. AI & THE “COMPUTATIONAL REVOLUTION”
• Algorithms: a set of instructions the describe the way to solve specific problems
• Machine learning: processes by which a computer can train and improve an
algorithm or computer model without step-by-step human involvement
• Artificial intelligence: the exhibition of intelligence by a machine
• Big Data & “ubiquitous computing” (eventually quantum computing)
• Robotics & “Internet of Things”
All these things build on each other = “combinatorial innovation”
Eventually, all sectors and all policy will be touched by the computational
revolution in some fashion.
4. PROFOUNDLY IMPORTANT TO OUR FUTURE
• The computational revolution has profound impact on global
competitive advantage & national security issues.
• Essential that U.S. maintains a leadership position in global
innovation
• We must:
1.Maximize the potential for innovation, entrepreneurialism,
investment, and worker opportunities (= promotional activities)
2.Develop a flexible governance framework to address various ethical
concerns about AI development (= governance activities)
9. What should the default
position be in debates over
innovation policy?
Precautionary Principle?
or
Permissionless Innovation?
10. “PERMISSIONLESS INNOVATION”
= the general freedom to experiment & learn through trial-and-
error
• openness to change, disruption, risk-taking
• avoids prior restraints on innovation; best-case thinking
• give entrepreneurs more green lights than red ones
• innovation innocent until proven guilty
• also called:
• “the innovation principle” / “the proactionary principle”
• “freedom to innovate”
11. THE “PRECAUTIONARY PRINCIPLE”
= crafting public policies to control or limit new innovations
until their creators can prove that they won’t cause any
harms.
• “better to be safe than sorry” mentality; worst-case
thinking
• gives entrepreneurs the red light
• preemptive policy restraints on innovation
• innovation basically guilty until proven innocent
12. THE CONFLICT OF VISIONS OVER INNOVATION
POLICY
Innovation should be free-wheeling must be carefully guided
Priority Spontaneity / experimentation Stability / equilibrium
Risk adaptation is preferred anticipation is preferred
Solutions
Reactive (ex post)
bottom-up remedies
Preemptive (ex ante)
top-down controls/solutions
Presumption “innocent until proven guilty” “guilty until proven innocent”
Ethos
“Nothing ventured, nothing
gained”
“Better to be safe than sorry”
Source: Adam Thierer, Mercatus Center
13. WHERE WILL INNOVATION DEFAULTS BE SET?
Top-down
(ex ante) Solutions
Bottom-up
(ex post) Solutions
Consumer protection
law
Common law
Torts
Contract/Property law
Social norms
New competition
Learning / Coping
Best practices
Educational efforts
Transparency
Sandboxes
Self-regulation
other “soft law”
Licensing
Permits
Restrictive defaults
Recall authority
Nudges
other mandates
Product bans
Entry barriers
Sales restrictions
State ownership
Censorship
Permissionless Innovation Precautionary Principle
Source: Adam Thierer, Mercatus Center
15. ISSUE DRIVERS FOR AI REGULATION
1) Fairness / Non-discrimination (“algorithmic
justice”)
2) Transparency / Explainability
3) Safety (both physical & mental) + Security
4) Privacy
5) Economic disruption / automation concerns
6) “Existential risk” (“runaway AI” / “killer robots”)
Challenge: How to define & enforce these amorphous
principles through regulation? And what it values
16. THE SOLUTION: ALIGNING AI & HUMAN VALUES
1) “Baking in” best practices and aligning AI design with
widely-shared goals and values; and,
2) Keeping humans “in the loop” at critical stages of this
process to ensure that they can continue to guide and
occasionally realign those values and best practices as
needed.
The Hard Question: Should this be accomplished through
top-down “hard law” regulation or bottom-up “soft law”
17. WHAT'S PAST (FOR THE NET)
IS PROLOGUE (FOR AI)??
WILL THE INTERNET MODEL
GOVERN?
18. U.S. INTERNET GOVERNANCE VISION
• early 1990s: commercial opening of the Net
• 1996: Telecom Act passes; keeps Internet largely free of old regs
• 1997: Framework for Global Electronic Commerce:
1. “the private sector should lead. The Internet should develop as a market driven
arena not a regulated industry.”
2. “governments should avoid undue restrictions on electronic commerce” & “parties
should be able to enter into legitimate agreements to buy and sell products and
services across the Internet with minimal government involvement or intervention.”
3. “where governmental involvement is needed,” the Framework continued, “its aim
should be to support and enforce a predictable, minimalist, consistent and simple
legal environment for commerce.”
lead to a strong role for soft law (especially multistakeholder processes) for digital
policy
20. INNOVATION FRAMEWORKS ACROSS
ADMINISTRATIONS SHARED MUCH IN
COMMON
1. Calls for expanded R&D funding; tax credits
2. Focus on strengthening STEM education
3. Calls for “re-skilling” workers for new jobs
4. General support for strong IP protection
5. Support for immigration policies that attract skilled labor (except
Trump)
6. General openness to risk-taking / entrepreneurialism & small biz
formation
7. “Light-touch” regulatory approaches & ex post enforcement efforts
8. Increased reliance on soft law and multistakeholder processes
21. AI VISION: OBAMA YEARS
“The way I’ve been thinking about the
regulatory structure as AI emerges is that,
early in a technology, a thousand flowers
should bloom. And the government should
add a relatively light touch, investing
heavily in research and making sure there’s
a conversation between basic research and
applied research.”
- President Obama (2016)
22. AI VISION: TRUMP YEARS
“We recognize that we don’t need to impose
preemptive, overly-burdensome, and
innovation-killing regulations to stay true to
our values. The United States is demonstrating
how this model of innovation works.”
- Michael Kratsios, US CTO (2019)
23. “SOFT LAW” ON THE RISE FOR EMERGING
TECH
= Informal, collaborative, experimental & constantly evolving
governance mechanisms
• Guidance documents
• “Sandboxes” (informal consultations) & soft nudges
• Multistakeholder processes
• Agency workshops & reports
• Best practices & codes of conduct
• Industry self-regulation, co-regulation & other collaborative efforts
Soft law has become the dominant modus operandi for modern technological
governance, at least in the United States.
25. CASE STUDY: SOFT LAW FOR AVS
Our “rules of the road” for AVs aren’t rules at all
Congress won’t act, so soft law fills the void
26. EX POST HARD LAW SUPPLEMENTS SOFT
LAW
Ex post (after-the-fact) enforcement schemes are an important part of
“permissionless innovation”
• Federal and state consumer protection statutes and agencies – “unfair &
deceptive practices” remedies; other consumer anti-fraud protections
• Product recall authority – NHTSA, CPSC, FDA all can recall defective products
• Common law – torts, class actions, product liability, negligence, design defects
law, failure to warn, breach of warranty, property law and contract law
• Whistleblower protections
• Other targeted statues – laws to address hardest problems after other remedies
exhausted
28. KEY AI POLICY STATEMENTS: CHINA & EU
China
• 2015: Made in China 2025 strategic plan
• 2017: A New Generation Artificial Intelligence Development Plan
European Union
• 2017: Civil Law on Robotics
• 2018: High-Level Expert Group on Artificial Intelligence (AI HLEG) formed
• 2018: General Data Protection Regulation (GDPR)
• 2018: Ethics Guidelines for Trustworthy AI
• 2019: Policy and Investment Recommendations for Trustworthy Artificial Intelligence
• 2020: White Paper on Artificial Intelligence
• 2020: Report on the Safety and Liability Implications of Artificial Intelligence, the Internet of Things,
and Robotics
• 2021: EU Artificial Intelligence Act
29. RECENT U.S. REGULATORY PROPOSALS
PRECAUTIONARY PRINCIPLE FOR AI
• Algorithmic Accountability Act
• Artificial Intelligence Initiative
Act
• Future of Artificial Intelligence
Act
• Advancing Artificial Intelligence
Research Act
• National AI Research Resource
Task Force Act
• Federal Robotics Commission
• AI Control Council
• National Algorithmic
Technology Safety Admin.
• National Technology Strategy
Agency
• “FDA for Algorithms”
Proposed Laws Proposed Agencies
30. BIDEN ADMIN CALL FOR “AI BILL OF
RIGHTS”
• “a Bill of Rights for an AI-Powered
World” to “guard against the
powerful technologies we have
created.”
• suggested need for “new laws and
regulations to fill gaps,” and that
“States might choose to adopt
similar practices.”
• launched the National Artificial
Intelligence Research Resource Task
Force to study issues
31. ALGORITHMIC AUDITING / AI IMPACT
ASSESSMENTS
= have developers conduct reviews of algorithmic systems to
evaluate how well they were aligned with various ethical values or
other commitments
• can help ensure organizations live up their promises
• already utilized in other fields to address safety practices, financial
accountability, labor practices and human rights issues, supply chain
practices & various environmental concerns.
• But, mandated? Or self-regulatory?
• One model: International Association of Privacy Professionals (IAPP) trains
and certifies privacy professionals through formal credentialing programs,
supplemented by regular meetings, annual awards, and a variety of outreach
and educational initiatives.
• We should use similar model for AI and start by supplementing Chief Privacy
32. THE “PACING PROBLEM” CHALLENGES REGULATION
Pace of
Change
Time
Technological
Change
Political
Change
Pacing
Problem
33. GETTING THE BALANCE RIGHT
• AI ethical concerns deserve serious consideration and appropriate
governance steps to ensure that these systems are beneficial to society.
• But there is an equally compelling public interest in ensuring that AI
innovations are developed and made widely available to help improve
human well-being across many dimensions.
• No need to worry about the future if inventors can’t even create it first!
• We need to strike this balance with humility and patience in mind.
• Flexible, agile governance deserves a chance before we bring in the
hammer of the Precautionary Principle.
34. LET’S GIVE INNOVATION A CHANCE
START AROUND HERE! … NOT HERE
Top-down
(ex ante) Solutions
Bottom-up
(ex post) Solutions
Consumer protection
law
Common law
Torts
Contract/Property law
Social norms
New competition
Learning / Coping
Best practices
Educational efforts
Transparency
Sandboxes
Self-regulation
other “soft law”
Licensing
Permits
Restrictive defaults
Recall authority
Nudges
other mandates
Product bans
Entry barriers
Sales restrictions
State ownership
Censorship
Permissionless Innovation Precautionary Principle
Source: Adam Thierer, Mercatus Center
35. ADDITIONAL READING FROM ADAM
THIERER
• Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom, 2nd ed. (2016).
• “Why the Future of AI Will Not Be Invented in Europe,” Technology Liberation Front, August 1, 2022.
• “Existential Risks & Global Governance Issues around AI & Robotics,” [DRAFT CHAPTER, July 2022].
• “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.
• “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).
• “Elon Musk and the Coming Federal Showdown Over Driverless Vehicles,” Discourse, November 22, 2021.
• “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021.
• “A Brief History of Soft Law in ICT Sectors: Four Case Studies,” Jurimetrics, Vol. 61 (Fall 2021): 79-119.
• “U.S. Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4 (2021).
• “The Worst Regulation Ever Proposed,” The Bridge, September 2019.
• “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Tech. Law Jour, Vol. 17 (2018).
• “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020.
• “Europe’s New AI Industrial Policy,” Medium, February 20, 2020.
• “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020.
• “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Vol. 61 (December 2018).
• “Artificial Intelligence and Public Policy,” Mercatus Research (2017).
• “Shouldn’t the Robots Have Eaten All the Jobs at Amazon By Now?” Technology Liberation Front, July 26, 2017.
• “The Day the Machines Took Over,” Medium, May 11, 2017.
• “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016.
• “Learning by Doing,” the Process of Innovation & the Future of Employment,” Technology Liberation Front, September 25, 2015.
