Exploring the effect of the information amount in explanation on different gaming expertise levels

Explainable AI (XAI) has gained increasing attention from more and more researchers with an aim to improve human interaction with AI systems. In the context of human-agent teamwork (HAT), providing explainability to the agent helps to increase shared team knowledge and belief, therefore improving overall teamwork. With various backgrounds and...

Interactive Model Explanations for Greater Intelligibility

As AI is progressively incorporated into several spheres of society. This rapid growth has also brought a lot of challenges such as discriminating or skewed results and a lack of accountability. To address these challenges, there is a growing interest in Human-AI teams where AI-assisted decision-making includes humans in the loop. This approach...

How truthful explanation of a conceder negotiation agent affects human trust, compared to a neutral one

Trust in negotiation agents plays a crucial role in their adoption and utilization. However, there is not enough research on what factors influence it. This paper aims to investigate how different explanations of a negotiation agent’s strategy affect human trust and decision-making. Specifically, it compares the effects of a truthful explanation...

Negotiating task allocation in a team with the help of a negotiator agent

This research experiment aimed to investigate the level of trust placed in an AI negotiation assistant paired with a truthful explanation of their negotiation strategy versus an opposite explanation within the Pocket Negotiator platform. A between-user study involving 30 participants was conducted to assess participants’ trust perceptions based...

The Effect of Different Explanations of Conceder Negotiation Style on the Trust between Humans and Agents

Negotiations have an essential role in our lives as they help us to find mutually beneficial solutions and resolve conflicts. It leads to effective communication and collaboration between the involved parties. Negotiation among parties has high importance to have an outcome that is suitable for all. In such scenarios, negotiation agents can be...

Why and How Should We Explain AI?

Why should we explain opaque algorithms? Here four papers are discussed that argue that, in fact, we don’t have to. Explainability, according to them, isn’t needed for trust in algorithms, nor is it needed for other goals we might have. I give a critical overview of these arguments, showing that there is still room to think that explainability...