Algorithms are the DNA of most modern and autonomous computational systems. They are “the mind of the autonomous system,” and as such, they allow for different hardware and software to learn, detect, and adapt to new digital contexts (London, 4691). Their genetic intelligence makes algorithms both generative and receptive parts of a digital architecture or ecosystem, and their ontology is such that they demand reciprocity. Facing the emergent complexities of this reciprocal relationship between autonomous technologies and their environment, scholars and practitioners alike are careful to couch the ethical problem of algorithms within the larger social context of network relations and value-systems. From the perspective of the readings, society and its principles still shape the reality and outcomes of AI. However, today’s algorithmic reality proves that in principles, ambiguities abound around their implementation, interoperability, relevance, and overall actionability. We might cut through this ambiguity by re-positioning control at the centre of the issue of AI; and this can be achieved by elevating reciprocity as the first-principle framework for all value-based approaches to AI.
Probably goes without saying, but this was a piece for class. So, I hope you stick around past the embedded citations and the formatting. God Bless :)