Ethics, Fairness and Bias in Accidental Collectives

This chapter explores aspects of ethics, fairness and social justice that relate these spaces to accidental collectives. The first section investigates the ethical consequences of accidental collectives’ development by critically examining the extent to which they can be regarded as fair and equal. The second part of the chapter discusses Floridi and Cowls’ Unified Framework of Five Principles for AI in Society as an important framework for assessing how AI may affect society, including information on how accidental collectives may adhere to or depart from these standards. The complex interactions between AI and fairness are the main topic of the third part of the chapter. In this, I examine the challenges posed by AI algorithms in ensuring fairness and preventing bias within accidental collectives. The focus of this part is on ethical issues related to decision-making procedures, data sources, and algorithmic openness. Finally, the future of accidental collectives over the next 10 to 50 years is explored in the final part of the chapter. Speculating across a spectrum that ranges from extreme AI evolution to more pragmatic and grounded developments, this section explores potential scenarios for the role of accidental collectives in society. The chapter concludes with the suggestion that the more we approach general artificial intelligence, the more accidentality in the generation of collectives lessen.