arxiv.org/abs/2302.04288 The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for … Continued
This is fairly specific to the AI Act being considered/written in the EU, but the thoughtful discussion is useful for understanding the challenges of regulating emerging AI technologies. Ryan 2302.02337 PDF Document · 396 KB Ryan Watkins, Ph.D.▲ Professor, George … Continued
AI advice is becoming increasingly popular, e.g., in investment and medical treatment decisions. As this advice is typically imperfect, decision-makers have to exert discretion as to whether actually follow that advice: they have to “appropriately” rely on correct and turn … Continued
2302.00813 PDF Document · 475 KB Value alignment problems arise in scenarios where the specified objectives of an AI agent don’t match the true underlying objective of its users. The problem has been widely argued to be one of the … Continued
Informed consent is a core cornerstone of ethics in human subject research. Through the informed consent process, participants learn about the study procedure, benefits, risks, and more to make an informed decision. However, recent studies showed that current practices might … Continued
Trust is often cited as an essential criterion for the effective use and real-world deployment of AI. Researchers argue that AI should be more transparent to increase trust, making transparency one of the main goals of XAI. Nevertheless, empirical research … Continued
Humans excel at causal reasoning, yet at the same time consistently fail to respect its basic axioms. They seemingly fail to recognize, for instance, that only the direct causes of an event can affect its probability (the Markov condition). How … Continued
A growing body of literature in fairness-aware ML (fairML) aspires to mitigate machine learning (ML)-related unfairness in automated decision making (ADM) by defining metrics that measure fairness of an ML model and by proposing methods that ensure that trained ML … Continued
In this current technological world, the application of machine learning is becoming ubiquitous. Incorporating machine learning algorithms on extremely low-power and inexpensive embedded devices at the edge level is now possible due to the combination of the Internet of Things … Continued
The dazzling promises of AI systems to augment humans in various tasks hinge on whether humans can appropriately rely on them. Recent research has shown that appropriate reliance is the key to achieving complementary team performance in AI-assisted decision making. … Continued