The paper, which looks into how the kind of expert giving the advice — i.e., a human or an AI advisor — influences trust, perceived responsibility, and reliance.

For more information about the paper, please check it out in our on-line library, over at the ACM Digital Library, and the video presentation prepared by Suzanne.

For your convenience you can also find the abstract right here:

While artificial intelligence (AI) is increasingly applied for decision-making processes, ethical decisions pose challenges for AI applications. Given that humans cannot always agree on the right thing to do, how would ethical decision-making by AI systems be perceived and how would responsibility be ascribed in human-AI collaboration? In this study, we investigate how the expert type (human vs. AI) and level of expert autonomy (adviser vs. decider) influence trust, perceived responsibility, and reliance. We find that participants consider humans to be more morally trustworthy but less capable than their AI equivalent. This shows in participants’ reliance on AI: AI recommendations and decisions are accepted more often than the human expert’s. However, AI team experts are perceived to be less responsible than humans, while programmers and sellers of AI systems are deemed partially responsible instead.

In the paper, Suzanne and team develop a taxonomy to categorize HRI failure types and their impact on trust. A risk score is introduced, as well as possible mitigation strategies to handle trust breaks of the user in a robotic system. The collaboration for this paper was a result of a workshop at Schloss Dagstuhl on ‘Ethics and Trust: Principles, Verification and Validation‘.

Are chat-bots going to take over all user interaction?

Prof. Abraham Bernstein in an Radio interview at the Swiss Public Radio:  Wirtschaftsmagazin «Trend» vom 1. Juli 2017 (starting about Minute 20).

On Tuesday, June 3, UZH Professor Abraham Bernstein and his former PhD student Prof. Katharina Reinecke (now at the University of Michigan) were awarded the European Research Paper of the Year Award  of 2014.

As the Web Site States:

The CIONET European Research Paper of the Year Election identifies the European research paper that embodies most excellence in both rigour and relevance of research. In order to promote the exchange of ideas, experiences and knowledge among professionals and academics in the area of information and communications systems and technology management, the CIONET European Research Paper of the Year acclaims a yearly best research paper.

The paper was chosen from the 28 papers published by European authors in either MISQ or ISR — the two top journals in information systems — which ensures that only top-rated research studies qualify. What makes the award especially remarkable is that the jury is entirely composed of CIOs. Hence, the award goes to a top research paper that has a profound practical impact.

This year’s jury comprised the following highly regarded CIOs: Carsten Trapp (SICK AG), Manuel Fischer (Amazon Europe), Edwin Erckens (Teva Pharmaceuticals Europe), Jean-Claude Blaimont (McCain Foods), Roberto Parra (CIONET Spain), Jorge Coelho (Portuguese Institute of Process Business Management), Frédéric Charles (Lyonnaise des Eaux/Suez Environnement), and Gerry Pennell (London Organising Committee for the Olympic and Paralympic Games) .

The paper called “Knowing What a User Likes: A Design Science Approach to Interfaces that Automatically Adapt to Culture” published in MISQ (PDF here) presents a method for automatically adapting to cultural differences between users. A brief interview with an explanation is available at o Youtube.

The award was announced at the CIOCITY annual convention of the European CIO association CIONET, which has roughly 4200 CIOs as members.

Full citation of the paper: Reinecke, Katharina and Bernstein, Abraham. 2013. “Knowing What a User Likes: A Design Science Approach to Interfaces that Automatically Adapt to Culture,” MIS Quarterly, (37: 2) pp.427-453.