The AI Element

Episode Guests

• 
  Ed Santow Australia’s Human Rights Commissioner
• 
  Christina Colclough Director of Platform and Agency Workers, Digitalisation and Trade at UNI Global Union
• 
  Neil Lawrence Professor of Machine Learning at the University of Sheffield

Show Notes

We don’t have enough control over our data—how it is collected, by whom, what it’s used for. We’re used to hitting “accept” to whatever agreement we need to use the online platforms, mobile apps and other digital services that run our daily lives. Yet public awareness is growing about the importance of privacy and data control. Major data breaches and scandals about the misuse of data have shown the failures of the private sector when it comes to self-regulation.

Now, governments and policymakers are stepping in with efforts to address the power imbalance between consumers and big companies when it comes to data. It’s about time — the impact of artificial intelligence could exacerbate that power imbalance, and help the data-rich get richer. Element AI’s Marc-Etienne Ouimette spoke with some of those leading the charge around taking back control of our data and the notion of data trusts — think a union, but for your data.

03:54 - NSW police may be investigated for ‘secret blacklist’ used to target children - The Guardian

08:30 - 94% of Australians do not read all privacy policies that apply to them – and that’s rational behaviour - The Conversation

09:16 - Click to agree with what? No one reads terms of service, studies confirm - The Guardian

10:57 - Up for Parole? Better Hope You’re First on the Docket - The New York Times

15:09 - The GDPR Covers Employee/HR Data and It's Tricky - Dickson Wright

18:01 - Companies are trying to test if they can make employees wear fitness trackers - Business Insider

20:03 - Silicon Valley & the Netherlands: Drivers of the future of automation - Netherlands in the USA

22:14 - Data Trusts - Neil Lawrence, inverseprobability.com

23:50 - Data trusts could allay our privacy fears - The Guardian

31:14 - Data trusts: reinforced data governance that empowers the public - Element AI

Further Reading

What is a data trust? - Open Data Institute

Data trusts: reinforced data governance that empowers the public - Element AI

Uncertainty and the Governance Dilemma for Artificial Intelligence - Dan Munro

Governing AI: Navigating Risks, Rewards and Uncertainty - Public Policy Forum

Anticipatory regulation - Nesta

Disturbing the ‘One Size Fits All’ Approach to Data Governance: Bottom-Up Data Trusts - Sylvie Delacroix & Neil Lawrence

Human Rights and Technology Issues - Australian Human Rights Commission

The Civic Trust - Sean McDonald & Keith Porcaro

Facebook’s privacy policy is longer than the US Constitution - The Next Web

Episode Guests

• 
  Nicole Rigillo Berggruen Research Fellow at Element AI
• 
  Cynthia Rudin Professor of Computer Science, Electrical and Computer Engineering, and Statistical Science at Duke University
• 
  Benjamin Thelonious Fels Founder of AI healthcare startup Macro-Eyes

Show Notes

“Explainability” is a big buzzword in AI right now. AI decision-making is beginning to change the world, and explainability is about the ability of an AI model to explain the reasons behind its decisions. The challenge for AI is that unlike previous technologies, how and why the models work isn’t always obvious — and that has big implications for trust, engagement and adoption.

Nicole Rigillo breaks down the definition of explainability and other key ideas including interpretability and trust. Cynthia Rudin talks about her work on explainable models, improving the parole-calculating models used in some U.S. jurisdictions and assessing seizure risk in medical patients. Benjamin Thelonious Fels says humans learn by observation, and that any explainability techniques need to take human nature into account.

01:11 - Facebook Chief AI Scientist Yann LeCun says rigorous testing can provide explainability

01:58 - Berggruen Institute, Transformation of the Human Program

05:34 - Judging Machines. Philosophical Aspects of Deep Learning - Arno Schubbach

06:31 - Do People Trust Algorithms More Than Companies Realize? - Harvard Business Review

08:25 - Introducing Activation Atlases - OpenAI

10:52 - Learning certifiably optimal rule lists for categorical data (CORELS) - YouTube

11:00 - CORELS: Learning Certifiably Optimal RulE ListS

11:45 - Stop Gambling with Black Box and Explainable Models on High-Stakes Decisions

16:52 - Transparent Machine Learning Models for Predicting Seizures in ICU Patients - Informs Magazine Podcast

19:49 - The Last Mile: Challenges of deployment - StartupFest Talk

24:41 - Developing predictive supply-chains using machine learning for improved immunization coverage - macro-eyes with UNICEF and the Bill and Melinda Gates Foundation

Further Reading

A missing ingredient for mass adoption of AI: trust - Element AI

Breaking down AI’s trustability challenges - Element AI

The Why of Explainable AI - Element AI

Episode Guests

• 
  Rediet Abebe Co-Founder and Co-Organizer of Black in AI, Co-Founder and Co-Organizer of Mechanism Design for Social Good
• 
  Charles C Onu Founder and AI Research Lead at Ubenwa

Show Notes

Charles C Onu is using AI to detect birth asphyxia in babies. His story is inspiring because of its impact on society and the field of healthcare (in 2016, 1,000,000 babies died from asphyxia), but also because of his humble beginnings. In this episode, Charles shows us that a passion for solving problems can help you overcome many obstacles.

Host Alex Shee also sits down with Rediet Abebe, Co-Founder and Co-Organizer of Black in AI, to expand on how others are using AI to change not just their industry, but the world.

Episode Guests

• 
  Daniel Gross Partner at Y Combinator and Head of the AI Track
• 
  Natacha Mainville Chief Innovation Officer at TandemLaunch
• 
  Jordan Fisher CEO at Standard Cognition
• 
  JF Gagné CEO of Element AI

Show Notes

Many have dystopian projections of what our future with AI will look like, but professionals working in AI see things differently. For some, our future with AI may simply mean more free time and cheaper access to quality services.

We check in with Jordan Fisher, Daniel Gross, Natacha Mainville and JF Gagné who together paint a picture of what a not-so-distant future might look, especially in retail and insurance. They may not know exactly what the year 2050 will look like, but they are hopeful.

Episode Guests

• 
  Frederic Michaud Former Director at Element AI
• 
  Oren Falkowitz CEO of Area 1 Security

Show Notes

Every touchpoint with a prospect is an opportunity to nurture that relationship, but also a potential entry point for hackers. Given that cybercriminals are more resourceful than ever, cybersecurity experts need to be just as sharp.

Oren Falkowitz is combining past experience at the NSA and US Cyber Command with AI to combat phishing attacks worldwide. In this episode, Alex Shee speaks to him and cybersecurity expert Frederic Michaud about how AI is currently being used to make businesses safer.

Episode Guests

• 
  Naomi Goldapple Former Program Director at Element AI
• 
  Chris Benson Chief Scientist for Artificial Intelligence & Machine Learning at Honeywell

Show Notes

Successful adopters of AI develop an AI-first strategy supporting all functional areas of the business: marketing, product development, customer support, sales, and beyond. What does this look like in practice? Naomi Goldapple consults with execs about AI strategy on the regular, provides some insight.

Alex also talks to Chris Benson who was hired at Honeywell to inject AI into the traditional-but-transforming manufacturing and logistics space. He shares some case studies of AI transformation and touches on the pervasive fear of job loss.

Episode Guests

• 
  JF Gagné CEO of Element AI
• 
  Natacha Mainville Chief Innovation Officer at TandemLaunch

Show Notes

As AI seeps into every industry, businesses are being forced to adapt. Old school industries may not be as lean or quick to pivot as startups, but they have access to a motherlode of funding and data. Still, red tape and outdated infrastructure may block them from the timely AI transformation they need to stay afloat tomorrow.

Alex Shee speaks with serial AI entrepreneur JF Gagné about this tension between startups and more corporate environments. Then, 15-year veteran of the insurance industry Natacha Mainville shares some real-world examples of how AI is flipping the industry on its head, forcing incumbents to keep up.

Episode Guests

• 
  Yoshua Bengio Co-Founder of Element AI and Scientific Director of the Montreal Institute for Learning Algorithms (MILA)
• 
  Daniel Gross Partner at Y Combinator and Head of the AI Track

Show Notes

Societal hype around AI is a byproduct of a few recent scientific breakthroughs — speech recognition, computer vision, natural language processing — in short, a computer’s ability to acquire human senses and mimic the human brain.

Element AI co-founder Yoshua Bengio, world-renowned professor and head of the Montreal Institute for Learning Algorithms, has been at the front lines of the Deep Learning Revolution that has enabled this kind of innovation. In this episode, he gives an overview of where the tech is actually at: how close is it to mirroring human senses?