For readers of Automated Trader there will be nothing mysterious about algorithms. Short strings of code, a secret sauce for trading; that's all. But in recent years social scientists have taken an intense interest in them. In 2015, the legal theorist Frank Pasquale published a book called 'The Black Box Society'. It focuses on the way that from Internet search engines to the algorithms that score our 'digital reputation', our lives are increasingly governed by opaque automated processes.
Within the academic community this has been called 'algorithmic governance'. Developing the work of the German sociologist Max Weber, who claimed that modern bureaucracies have locked us in an invisible 'iron cage', scholars see algorithms as taking society in troubling new directions. Algorithms watch, record and judge every aspect of our lives; and yet, most of us know little or nothing about them.
This is why a rule in the German High Frequency Trading Act ('HFT Act') requiring firms to tag their algorithms with a numerical code caught my interest. Here the notion of algorithmic governance was turned on its head: the regulation does not concern surveillance of humans by algorithms, but surveillance of algorithms by humans. The idea behind the rule was that it would allow trade surveillance officers to see algorithms at work in exchanges' order books. As a result, it was believed that the flash crashes and market manipulations that have proven difficult for regulators to make sense of could be more easily investigated; light would be shed on automated markets.
From my perspective, more interesting were the philosophical questions the rule raised. In particular, the HFT Act's requirement that firms identify the algorithm responsible for an order implies that we have a clear idea about what an algorithm is. But do we? I searched high and low, scouring the philosophical and computer science literature, but did not discover a satisfactory answer. My initial response to the tagging rule was therefore incredulity. It seemed like just another instance of regulatory naivety, destined to fall short of expectations.