In: Society, Science, Technology
AI & Ethics
Technological advancements pose new and unprecedented ethical questions that humanity will have to deal with. The world will surely not become a better place if our conscious or unconscious biases make their way into algorithms. AI should be fair. In the end, it comes down to this: Do we want to model the world as it is, or as it should be?
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Summaries
A.I. Is Mastering Language. Should We Trust What It Says?
OpenAI’s GPT-3 and other neural nets can now write original prose with mind-boggling fluency – a development that could have profound implications for the future.
New York Times Magazine, 2022
Meet DALL-E, the A.I. That Draws Anything at Your Command
New technology that blends language and images could serve graphic artists – and speed disinformation campaigns.
The New York Times, 2022
Responsibility: Responsible AI in Action
Microsoft AI Business School Podcast Episode 3
Microsoft, 2020
Ethicists were hired to save tech’s soul. Will anyone let them?
Firms are adding ethical thinking to their processes, but ethical outcomes are optional.
Protocol, 2020
An AI Tool to Make Clinical Trials More Inclusive
An artificial-intelligence tool called Trial Pathfinder can run clinical-trial emulations using healthcare data from people with cancer, and can learn how to optimize trial-inclusion eligibility criteria, while maintaining patient safety.
Nature, 2021
Daniel Kahneman and Yuval Noah Harari in Conversation
Top Global Historical Trends Shaping Humankind Today
sponsor Landmark Bank, 2021
Resisting the Rise of Facial Recognition
Growing use of surveillance technology has prompted calls for bans and stricter regulation.
Nature, 2020
Beating Biometric Bias
The technology is improving – but the bigger issue is how it’s used.
Nature, 2020
Four Ethical Priorities for Neurotechnologies and AI
Artificial intelligence and brain–computer interfaces must respect and preserve people’s privacy, identity, agency and equality, say Rafael Yuste, Sara Goering and colleagues.
Nature, 2017
Design AI so that it’s Fair
Identify sources of inequity, de-bias training data and develop algorithms that are robust to skews in data, urge James Zou and Londa Schiebinger.
Nature, 2018
