Artificial Intelligence and You

Never mind fantasies about Skynet and Terminators; how to trust AI is a real issue right now, as AI is used in life-impacting decisions like medical diagnoses and loan granting. Kush Varshney has a PhD from MIT and is a distinguished researcher at IBM’s Thomas J. Watson Research Center in New York, where he leads the machine learning group in the Foundations of Trustworthy AI department. He is the author of the book Trustworthy Machine Learning. We talk about the whole ecosystem of trustworthiness, finding out where it goes in areas like privacy, anonymization, regulation, compliance, and oversight.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

Joining us from Dubai is Tannya Jajal, keynote speaker, AI futurist, and UAE Chapter Lead for the Global Women in Tech Movement. She is a resource manager at VMware, a technology contributor at Forbes Middle East, and author of the new book, Thinking Machines: AI and the Intelligence Explosion.

I invited Tannya to the podcast after running into her on two different AI panels in different countries on the same day (virtually!). We talk about how AI is being taught and developed in the worlds of women, children, and the Middle East.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

On our last show of 2021, it's time to think about the year ahead, and for that I have a panel of amazing experts!

• Richard Foster-Fletcher, founder of MKAI, the inclusive Artificial Intelligence Community, advisor to the United Nations Environmental Programme and UN Framework Convention on Climate Change;
• Ben Goertzel, chief scientist of Hanson Robotics and author of Ten Years To the Singularity If We Really Really Try;
• Katie King, speaker and marketing consultant, and author of the 2022 book AI Strategy for Sales and Marketing: Connecting Marketing, Sales and Customer Experience ;
• Prashant Natarajan, VP of Strategy & Products at H2O.ai and author of Demystifying AI for the Enterprise.

It's a free-ranging, free-spirited, free-for-all as we talk about the past and future trajectory of COVID effects on technology adoption, the evolution of attitudes towards, and equality in, AI, changes in the environmental impact of AI, and more. This is high quality thinking from people at the coal face of the industry, giving you their best shots at information you can use for the year ahead. Happy New Year!

Transcript and URLs referenced at HumanCusp Blog.

What do you, a citizen, need to know and do about AI in your life now and in the future? Enter the author of The Adaptable Mind; John Zerilli is a philosopher, a Leverhulme Fellow at the University of Oxford, a Research Associate in the Oxford Institute for Ethics in AI, and an Associate Fellow in the Centre for the Future of Intelligence at the University of Cambridge.

We talk about his 2021 book A Citizen's Guide to Artificial Intelligence, which spells out the categories in which we should pay attention. In part 2, we'll be talking about bias, how education should address AI, and more.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

What do you, a citizen, need to know and do about AI in your life now and in the future? Enter the author of The Adaptable Mind; John Zerilli is a philosopher, a Leverhulme Fellow at the University of Oxford, a Research Associate in the Oxford Institute for Ethics in AI, and an Associate Fellow in the Centre for the Future of Intelligence at the University of Cambridge.

We talk about his 2021 book A Citizen's Guide to Artificial Intelligence, which spells out the categories in which we should pay attention. In part 1, we'll be talking about what he wants to achieve with the book and how some of those issues, in particular, privacy, impact the average person today.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

How could you know which countries are doing a good job with artificial intelligence, and which sites are the worst disinformation spreaders? Sounds incredibly useful but impossible to figure out, right? Alexandra Mousavizadeh of Tortoise Media in London has founded global indexes that answer those and other questions: The Global AI Index, the Responsibility100 Index, and the Global Disinformation Index. As Director of the Tortoise Intelligence team, her insights into geopolitical and industry conflicts and state of the art are highly prized by governments and multinationals.

In part 2, we talk about China's race for AI gold, and the global disinformation index.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

How could you know which countries are doing a good job with artificial intelligence, and which sites are the worst disinformation spreaders? Sounds incredibly useful but impossible to figure out, right? Alexandra Mousavizadeh of Tortoise Media in London has founded global indexes that answer those and other questions: The Global AI Index, the Responsibility100 Index, and the Global Disinformation Index. As Director of the Tortoise Intelligence team, her insights into geopolitical and industry conflicts and state of the art are highly prized by governments and multinationals.

In part 1, we talk about the methodologies behind the indexes, their relationship to ESG, inequality, and the labor markets.

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.

Training an AI to render accurate decisions for important questions can be useless and dangerous if it cannot tell you why it made those decisions. Enter explainability, a term so new that it isn't in spellcheckers but is critical to the successful future of AI in critical applications.

Michael Hind is a Distinguished Research Staff Member in the IBM
Research AI department in Yorktown Heights, New York.  His current
research passion is the area of Trusted AI, focusing on governance,
transparency, explainability, and fairness of AI systems.  He helped launch several successful open source projects, such as
AI Fairness 360 and AI Explainability 360.

In part 2, we talk about the Teaching Explainable Decisions project, some of Michael’s experience with Watson, the difference between transparency and explainability, and a lot more. 

All this plus our usual look at today's AI headlines.

Transcript and URLs referenced at HumanCusp Blog.