Francesca Rossi

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Francesca Rossi
Francesca Rossi.jpeg
Born (1962-12-07) December 7, 1962 (age 60)
Ancona, Italy
Alma mater University of Pisa
Scientific career
Fields Artificial intelligence
Institutions

Francesca Rossi (born December 7, 1962) is an Italian computer scientist, currently working at the IBM Thomas J. Watson Research Center (New York, USA) as an IBM Fellow and the IBM AI Ethics Global Leader.

Contents

Education and career

She received her bachelor's and master's degrees in computer science from the University of Pisa in 1986, and a PhD in computer science from the same university in 1993. After her graduation, she stayed at the University of Pisa as an assistant professor until 1998. She then moved to the University of Padova where she was an associate professor until 2001, and a full professor until 2018. In 2014–2015 she was on sabbatical as a Fellow of the Radcliffe Institute for Advanced Studies, Harvard University. In 2015 she joined IBM Research, at the T.J. Watson IBM Research Center (New York, USA), as a distinguished researcher. In 2020 she became an executive and was appointed as an IBM Fellow. [1]

Research interests

Her research interests are in the area of artificial intelligence, with particular focus on constraint programming, combinatorial optimization, preference modeling, reasoning, and aggregation, knowledge representation, constrained reinforcement learning, ethically aligned AI, neuro-symbolic AI, and cognitive AI architectures. In the past, she has also worked on language semantics, graph grammars, logic programming, and Petri nets. She is also interested in understanding how to embed ethical principles into decision-making systems, to support either individuals or groups make more ethical decisions. Topics of special attention, in this regard, are detecting bias, defining distances between preference models, as well as embedding ethical behavioral constraints into reinforcement learning models. Most recently, her research interest is in leveraging cognitive theories of human reasoning and decision making, such as the thinking fast and slow theory of Daniel Kahneman, to advance AI's capabilities.

On these topics, she has published over 230 articles in international journals and conferences. [2] She has also edited over 20 volumes, including the Handbook of Constraint Programming. She co-authored the book "A Short Introduction to Preferences: Between Artificial Intelligence and Social Choice", published in the Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, July 2011, and she authored the book "Il confine del futuro – Possiamo fidarci dell'Intelligenza Artificiale?", published by Feltrinelli for the Italian market.

Awards, honors, and appointments

AI Ethics roles

Francesca is a leader in the field of AI ethics, both with her AI research projects aimed at embedding human values in AI systems and the many roles she has had, or currently has, in this area:

TEDx Talks

Francesca has delivered 4 TEDx talks, on topics related to AI:

Podcasts

She has delivered several online talks and podcast, including "Fast and Slow AI", [4] Francesca Rossi and Daniel Kahneman, CERN SPARK, 2021

Media coverage

Francesca has been interviewed by several prominent media venues, including: D di Repubblica (May 2021), The Nikkei (June 2021), Insider: Inside the Technology (September 2021), Fortune (December 2021), The Financial Times (Sept. 2018), The Nikkei (Jan. 2018), The Economist (June 2016), The Washington Post (May 2015), the Wall Street Journal (May 2015), Sydney Morning Herald (Feb. 2015), Euronews (Jan. 2015).

She has also written some pieces for the media, such as:

Related Research Articles

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References

  1. "2020 IBM Fellows" . Retrieved 9 March 2022.
  2. Francesca Rossi at DBLP Bibliography Server OOjs UI icon edit-ltr-progressive.svg
  3. "Fellows | European Association for Artificial Intelligence". www.eurai.org. Retrieved 2019-10-28.
  4. "Fast and Slow AI".
  5. Rossi, Francesca (5 November 2020). "How IBM is Working Towards a Fairer AI". Harvard Business Review.