"We’re at the beginning of a new era in government — one where governance is software-defined." -- Hemant Taneja (Managing Director at General Catalyst)
Join us for the launch of the Tech 2025 Live Chat series (in our new Think Tank Forum!) as we tackle a topic that is undoubtedly one of the biggest problems facing the world as governments and private companies race to develop and implement Artificial Intelligence (AI). The big question we'll be exploring is:
What should we do when AI algorithms, used by local governments, deny us vital services and opportunities, or unjustly condemns us, on the basis of our personal life choices, age, race, or sex?
Algorithms are already exhibiting shocking biases that are having devastating consequences on the human beings they are supposed to serve. This disturbing fact, coupled with the AI "black box" (where algorithms make seemingly counter-intuitive, potentially damaging decisions that researchers and developers do not understand -- and which algorithms can't explain) means we are quite possibly facing a level of uncertainty and potential upheaval in society that is unprecedented. How should local governments and ordinary citizens, working together, address this growing threat?
In this forum live chat, Anne T. Griffin, a human and Product Manager (in that order) and Emerging Tech Correspondent at Tech 2025, will host a thought-provoking discussion on this topic, with an emphasis on the NYC Algorithmic Biases Bill, that will ask us to explore the limits of our tolerance for algorithmic biases and consider a system of transparency and accountability for local governments that are increasingly using algorithms to decide our fate and who gets life-saving services. Anne, who is passionate about ensuring that algorithms are developed and implemented fairly and that they are held accountable when they aren't, explored this very topic in a recent Tech 2025 blog post: Holding Algorithms Accountable to Those They Should Be Serving
Some of the talking points we'll cover include:
- Is there a uniform definition of "algorithmic fairness" and, if not, should there be and who should define it?
- How can we know when algorithms are biased?
- With even experts and developers of algorithms grappling to understand their impact, how should we educate the general public so that they can participate in this discourse substantively?
- The pros and cons of predictive policing;
- Real life examples where algorithms made biased decisions that caused detrimental harm to a human being;
- Who should be held accountable when algorithms discriminate?
- How are other countries dealing with algorithmic transparency and accountability?
- If we can't know what's in the black box, what should we do to mitigate damages?
- The City of NY Launched
- What can all of us do now to steer this ship away from the iceberg?
- What are biased algorithms teaching us about ourselves?
We are all learning about this topic as we go (even the experts are grappling to understand all of this!). Our chats are open to members with all-levels of knowledge in this space. But we want to also have an informed discussed where we are at least all aware of how the topic is being defined and discussed by experts and the mainstream media. Whether you're an expert in AI or completely new to this, the following articles will quickly get you up to speed on this topic. We will likely discuss or reference many of these articles (to some extent) during the chat:
1. How Artificial Intelligence is Transforming the World (Brookings)
2. The Dark Secret at the Heart of AI: No one really knows how the most advanced algorithms do what they do. That could be a problem. (MIT Technology Review)
3. Holding Algorithms Accountable to Those They Should Be Serving (by Anne T. Griffin)
3. New York City Passes Bill to Study Biases in Algorithms Used by the City (Motherboard)
4. A round up of robotics and AI ethics: part 1 principles (Robo Hub)
5. Artificial intelligence could identify gang crimes—and ignite an ethical firestorm (Science Magazine)
6. Can ‘predictive policing’ prevent crime before it happens?
7. Tweet Chat with Kate Crawford on Consumer Protections and AI (Twitter)
8. What Happens When an Algorithm Cuts Your Healthcare? (The Verge)
9. How Can We Reveal Bias in Computer Algorithms? (video included) (The Regulatory Review)
10. New Research Aims to Solve the Problem of AI Bias in “Black Box” Algorithms (MIT Review)
11. Opinion: Artificial intelligence is too powerful to be left to Facebook, Amazon and other tech giants (Market Watch)
12. Stanford researchers use machine-learning algorithm to measure changes in gender, ethnic bias in U.S. (Standford News)
13. Algorithmic Impact Assessment: a Practical Framework for Public Agency Accountability (a report by AI Now)
14. Palintir Has Secretly Been Using New Orleans to Test Its Predictive Policing Technology (The Verge)
15. Machine Bias - There’s software used across the country to predict future criminals. (ProPublica)
16. UK report urges action to combat AI bias (Tech Crunch)
About Anne T. Griffin
Anne (@annetgriffin) is a human and product manager, in that order, who studied engineering at the University of Michigan. She is passionate about the human aspects of technology and building machine learning and AI products rooted in the realities of the human experience. She is also an Emerging Tech Correspondent for Tech2025, a platform and community for learning about, and discussing emerging technologies such as AI. Empathy at a product level and a cultural level is a key value. Her current focus is to explore what "fairness" means at a product level and how teams can integrate empathy and awareness of the impact of bias into the creative and development process. She has worked with major companies such as Microsoft, Mercedes-Benz, American Express, Comcast, and Colgate-Palmolive.
Join the Chat and Offer Feedback
To join the chat, RSVP below and we'll send you a link to the forum page where the chat will be held and a reminder to attend. Do you have questions you'd like to submit to the discussion, books/articles/video you'd like to suggest, or any information you'd like us to consider that will make chat even more informative and engaging? Submit your suggestion below when you RSVP to the chat. We'll post questions in the forum a few days before the chat where everyone will be able to vote on the top 5 questions they'd like addressed first (soooo diplomatic 😎).
Let's do this!