Google’s rapid-fire launches seems to have caught up with them. First complaints about Gemini’s image generation surfaced and the feature was disabled due to what seems to have been hurried implementation (and ‘hard-coded’ some instructions to generate diverse ethnicities no matter the context). But soon Gemini’s more complex language responses were being highlighted by those who saw a pattern of anti-white bias. Rushing to release Gemini, Google have clearly given themselves little time to refine their strategy for dealing with contentious issues. Whilst its impossible for models to stay neutral in all situations, especially given biases inherent in human generated training data and human led reinforcement learning processes, OpenAI have had time to developed a more effective gameplan. In these situation GPT-4 seems to prefer short matter-of-fact responses reducing the chance of being caught-out on complex issues, and generally dialling down the heavy handed refusals. Gemini is prone to taking excessively complex standpoints, refusing tasks and delivering a lecture to the user for good measure. A red rag to those sensitive to culture war issues. The fallout from this episode may be behind the delayed July launch planned for the hotly anticipated release of Meta’s Llama 3, which some suggest has been found to be ‘too safe’ in testing and is being ‘loosened’ up as we speak!
Takeaway: The key point here is that aligning or steering an AI (or rather a giant seesawing stack of a trillion parameters) has moved forward in the last few years, but is never going to be an exact science, especially as models become ever larger. We will need to accept that just like not being able to align with every colleagues world views, we’re going to have to collaborate with models that have many viewpoints. Demis Hassabis, head of Google DeepMind has been on a media round in recent days. He talks about AI with a level of clarity and experience few can match, but also intones confidently about the mechanisms in place to protect us all from rouge AI. Hopefully this chapter will remind us all that what’s needed to manage these hugely complex creations should never be underestimated.