Four Responsibility Gaps with Artificial Intelligence: Why they Matter and How to Address them

The notion of “responsibility gap” with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four interconnected problems – gaps in culpability, moral and public accountability, active responsibility—caused by different sources, some technical, other organisational, legal, ethical, and societal. Responsibility gaps may also happen with non-learning systems. The paper clarifies which aspect of AI may cause which gap in which form of responsibility, and why each of these gaps matter. It proposes a critical review of partial and non-satisfactory attempts to address the responsibility gap: those which present it as a new and intractable problem (“fatalism”), those which dismiss it as a false problem (“deflationism”), and those which reduce it to only one of its dimensions or sources and/or present it as a problem that can be solved by simply introducing new technical and/or legal tools (“solutionism”). The paper also outlines a more comprehensive approach to address the responsibility gaps with AI in their entirety, based on the idea of designing socio-technical systems for “meaningful human control", that is systems aligned with the relevant human reasons and capacities.

How Emotions Modulate Arithmetic Performance

The goal of the present study was to test whether and how emotions influence arithmetic performance. Participants had to verify arithmetic problems. True problems were either easier or harder problems. False problems were parity-match or parity-mismatch problems. The odd/even status of proposed and correct answers was the same in parity-match problems (e.g., 19 × 7 = 131) and different in parity-mismatch problems (e.g., 17 × 9 = 152). Before each problem, participants saw a positive (e.g., smiling baby), negative (e.g., mutilations), or neutral pictures (e.g., neutral face) selected from International Affective Picture System (IAPS). They had to decide whether each picture includes a person or not before verifying each arithmetic problem. Results showed different effects of emotion on true- and false problem verification. Participants’ performance on true problems showed decreased problem-difficulty after processing negative pictures and increased difficulty effects after processing positive pictures. On false problems, we found smaller parity-violation effects after negative pictures (i.e., decreased performance on parity-mismatch problems), together with larger parity-violation effects after positive pictures (i.e., decreased performance on parity-match problems). These findings suggest that emotions influence arithmetic performance via which strategy is used and how each strategy is executed on each problem. They have important implications for understanding the role of emotions on arithmetic performance, and more generally on how emotions influence cognition.

Numerical Analysis of Elastic Contact between Coated Bodies

Substrate protection by means of a hard coating is an efficient way of extending the service life of various mechanical, electrical, or biomedical elements. The assessment of stresses induced in a layered body under contact load may advance the understanding of the mechanisms underlying coating performance and improve the design of coated systems. The iterative derivation of contact area and contact tractions requires repeated displacement evaluation; therefore the robustness of a contact solver relies on the efficiency of the algorithm for displacement calculation. The fast Fourier transform coupled with the discrete convolution theorem has been widely used in the contact modelling of homogenous bodies, as an efficient computational tool for the rapid evaluation of convolution products that appear in displacements and stresses calculation. The extension of this technique to layered solids is tantalizing given that the closed-form analytical functions describing the response of layered solids to load are only available in the frequency domain. Whereas the false problem periodization can be treated as in the case of homogenous solids, the aliasing phenomenon and the handling of the frequency response function in origin require adapted techniques. The proposed algorithm for displacement calculation is coupled with a state-of-the-art contact solver based on the conjugate gradient method. The predictions of the newly advanced computer program are validated against existing results derived by a different method. Multiple contact cases are simulated aiming to assess the influence of coating thickness and of its elastic properties on the contact parameters and the strass state. The performed simulations prove that the advanced algorithm is an efficient tool for the contact analysis of coated bodies, which can be used to further understand the mechanical behavior of the coated system and to optimize its design.