Hi Anna, thanks for taking part. Please could you tell us a bit about your practice?
I am an artist who has been working with machine learning for a few years. I’m really interested in working with collections of information, particularly self-generated data sets, to create new and unusual narratives in a variety of mediums, and what happens when things cannot fit into discrete categories. At the moment I’m working on the intersection of machine learning and nature and what we can learn from history.
What are the questions you’re interested in raising through your practice, and why is it important we have these conversations now?
I think it is really important to start to unpick all of the processes that sit behind machine learning – we’re at this moment where we can see things breaking and have a chance a question the assumptions that sit behind them before they get codified into society.
What does ‘voice’ mean to you in the context of technology and digital culture?
Voices are so interesting, in particular accents. We can hear and interpret almost instantly someone’s gender, age, education levels, social class when they speak. We know that we judge based on appearances, but we equally judge based on voice. Now, these judgements are being built into algorithms. For example, speech-to-text conversion platforms powered by machine learning can return transcripts of what it thinks it has heard and a score of how “confident” it is that the transcription is correct. Confidence is based on how close the speaker is to those in its training set, the adherence to its perceived norm. The idea of a linguistic norm is loaded as it privileges one form of speaking over another. It’s these sorts of things that I think we should be thinking about now, because as the programme becomes more smooth, it also becomes easier to ignore, and as it becomes easier to ignore, it also becomes easier not to question the assumptions around correctness in accent and dialect that sit behind it.
The future is increasingly driven by algorithms… should we be concerned?
Algorithms are essentially ‘rule’, and the world has always been driven by rules. I think the thing that is a little bit worrying now is that while before the rules were open and obvious, now it is much harder to understand how an algorithm works.
In the world of tech and digital culture right now, what do you see as the most exciting opportunities and the biggest challenges or fears/concerns?
I think the speed that new technology is developing is a challenge – there is less and less time to really think through the consequences and effects of what we are doing – but it is also an opportunity to solve some of the biggest problems.
Image: Myriad (Tulips) 2018, Anna Ridler (image credit: Emily Grundon)