Abstract

This special issue (in cooperation with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Technology and Society Magazine</i> , December 2021) is dedicated to examining the governance of artificial intelligence (AI) through soft law. This kind of law is considered “soft” as opposed to “hard” because it comes in the form of governance programs whose goal is to create substantive expectations that are not directly enforceable by government <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> . Soft law materializes out of necessity to enable a technological innovation to thrive and not be hampered by disparate heterogeneous practices that may negatively impact its trajectory, causing a premature “valley of death” exit scenario <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> . Soft laws are meant to be “just in time” to grant industry fundamental guidance when dealing with complex socio-technical assemblages that may have significant socio-legal implications upon diffusion into the market. Anticipatory governance is closely connected with soft law, in that intended and unintended consequences of a new technology may well be anticipated and proactively addressed <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> .

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