One day workshop on Responsible Artificial Intelligence
The speakers brought up many interesting issues such as (a) LLMs and the prevalence of convincing (both intentionally and unintentionally) false information; (b) The lack of a common understanding of fairness across disciplines, the role of education and the need for awareness; (c) Ethical dilemmas such as whether we should value privacy and avoid disclosing sensitive information even in cases of lives being at risk; (d) Trust, openness about how data are collected, specification about the model (open source?); (e) Concerns that professionals will overly rely on AI which will affect their competence, e.g., pilots less comfortable in flying a plane manually or doctors that depend too much on automatic diagnostic systems.
One day workshop on Responsible Artificial Intelligence
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Introduction to Algorithmic Fairness |
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Preventing Undesirable Behavior of Intelligent Machines |
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Algorithmic Fairness in Recommender Systems |
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Diversity and Fairness in Data Selection |
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Fairness by design as the core principle of responsible AI |
