Aimee van Wynsberghe

Artificial intelligence (AI) is becoming increasingly important for the infrastructures that support many of society’s functions. Transportation, security, energy, education, the workplace, the government have all incorporated AI into their infrastructures for enhancement and/or protection. In this paper, we argue that not only is AI seen as a tool for augmenting existing infrastructures, but AI itself is becoming an infrastructure that many services of today and tomorrow will depend upon. Considering the vast environmental consequences associated with the development and use of AI, of which the world is only starting to learn, the necessity of addressing AI alongside the concept of infrastructure points toward the phenomenon of carbon lock-in. Carbon lock-in refers to society’s constrained ability to reduce carbon emissions technologically, economically, politically, and socially. These constraints are due to the inherent inertia created by entrenched technological, institutional, and behavioral norms. That is, the drive for AI adoption in virtually every sector of society will create dependencies and interdependencies from which it will be hard to escape. The crux of this paper boils down to this: in conceptualizing AI as infrastructure we can recognize the risk of lock-in, not just carbon lock-in but lock-in as it relates to all the physical needs to achieve the infrastructure of AI. This does not exclude the possibility of solutions arising with the rise of these technologies; however, given these points, it is of the utmost importance that we ask inconvenient questions regarding these environmental costs before becoming locked into this new AI infrastructure.

‘Sustainable AI’ sets itself apart from other AI ethics frameworks by its inherent regard for the ecological costs of AI, a concern that has so far been woefully overlooked in the policy space. Recently, two German-based research and advocacy institutions have published a joint report on Sustainability Criteria for Artificial Intelligence. This is, to our knowledge, the first AI ethics document in the policy space that puts sustainability at the center of its considerations. We take this as an opportunity to highlight the foundational problems we see in current debates about AI ethics guidelines. Although we do believe the concept of sustainability has the potential to introduce a paradigm shift, we question whether the suggestions and conceptual grounding found in this report have the strength to usher it in. We show this by presenting this new report as an example of current approaches to AI ethics and identify the problems of this approach, which we will describe as ‘checklist ethics’ and ‘ethics of carefulness’. We argue to opt for an ‘ethics of desirability’ approach. This can be completed, we suggest, by reconceptualizing sustainability as a property of complex systems. Finally, we offer a set of indications for further research.

A growing body of research can be found in which roboticists are designing for reciprocity as a key construct for successful human–robot interaction (HRI). Given the centrality of reciprocity as a component for our moral lives (for moral development and maintaining the just society), this paper confronts the possibility of what things would look like if the benchmark to achieve perceived reciprocity were accomplished. Through an analysis of the value of reciprocity from the care ethics tradition the richness of reciprocity as an inherent value is revealed: on the micro-level, as mutual care for immediate care givers, and on the macro-level, as foundational for a just society. Taking this understanding of reciprocity into consideration, it becomes clear that HRI cannot achieve this bidirectional value of reciprocity; a robot must deceive users into believing it is capable of reciprocating to humans or is deserving of reciprocation from humans. Moreover, on the macro-level, designing social robots for reciprocity threatens the ability and willingness to reciprocate to human care workers across society. Because of these concerns, I suggest re-thinking the goals of reciprocity in social robotics. Designing for reciprocity in social robotics should be dedicated to the design of robots to enhance the ability to mutually care for those that provide us with care, as opposed to designing for reciprocity between human and robot.