According to the latest Australian Responsible AI Index, there remains a significant gap between the intentions and realities of Responsible AI programs. This gap has remained fairly consistent since the first version of this study was commissioned. What this demonstrates, which is echoed globally, is that there is reasonable agreement on the ‘ethical principles’ that ought to ‘guide’ Responsible AI development and use. What this also shows is that organisations, for many reasons, are struggling to effectively interpret, implement, and operationalise said principles across the entire Responsible AI development and use lifecycle (something that cannot of course be separated from the broader organising structure and paradigm that gives rise to it).
Many responses to this problem, often framed as the ethical intent to action gap or ‘values gap’, have been proposed. These include greater board awareness, AI literacy work, standards development, and framework implementations, to name a few. All of this (and more) seems to be both valuable and necessary if society is to most benefit from Responsible AI. Yet, what is often missing from proposed responses to the ethical intent to action gap is deeper consideration for actually ‘doing ethics’.
Merely referencing principles, or attempting to encode a principle into a model, is not ethics. Ethics is the deliberative process of reflecting on our first order moral beliefs (ethical principles) in an attempt to do what is most good and right in a given situation. Arguably it is a cognitive process, where cognition is embodied, embedded, enacted, extended, emotional and exapted (6E CogSci). In this way, ‘doing ethics’ requires teams, organisations and society at large to explore what truly matters, define explicit and implicit values, explore how these values relate to and come into tension with one another, engage in diverse and inclusive dialogue, exploration and experimentation to productively explore tensions and tradeoffs, then use such collective bodies of work to inform how a given initiative proceeds (or doesn’t).
My experience leads me to believe that such work is largely missing from many Responsible AI programs within organisations. In short, there is a very significant risk that the real, challenging and confronting work of ‘doing ethics’ is skipped in favour of simpler approaches that lead to avoidable unintended consequences and further systemic ecological overshoot.
TL;DR summary… A heck of a lot of ‘can’, and sweet FA ‘should’.
In light of this, and off the back of being asked to record a short video for a big festival later this year, I offer you this brief musing on the power of ought before can. I only had four minutes, so I’ve kept it light and pretty darn accesible.
I trust it encourages some good pondering.