Bing’s Basilisk: Is Microsoft’s New Chatbot Really Evil?

We Need to Talk About Bing….

So, Bing AI is not quite the existential threat some social media users are presenting it as, and in fact with its search assistant functionalities Bing is likely going to constitute a pretty common part of the daily lives of all future internet users. That said, users on Reddit, Twitter, and from major new outlets have still been quite alarmed by some of Bing chatbot’s erratic content – which has even included admitting to spying on Microsoft employees and calling one user a short, ugly fascist. This does raise some really interesting questions about how people actually feel about the rise of AI, as it is quite reasonable to expect these kind of mass AI discourse events to have some level of influence on where and when tools like language models will be applied in the future – particularly by businesses who need to be cautious of the influence AI usage might have on their public image.

Before we get into this though, it’s important to again explain why Bing seems to be going rogue. In short, the problem is the internet. Language models are trained on vast datasets, containing text scraped from all over the world wide web. Many of these sources feature controversial and combative language, and some even describe the very kind of all powerful, vengeful AI that some commentators are casting Bing as. When you combine this with the difficulty of predicting language model outputs, it is no real surprise that Bing AI chatbot sometimes fires off bizarre responses to seemingly innocuous questions like ‘when can I watch Avatar 2’. It’s crucial to remember that as Bing chatbot develops, and especially as users use the ‘dislike’ feedback option to mark out inappropriate responses, these kinds of problems will become much less common. In fact, Microsoft have already taken the step of limiting Bing AI’s chat duration to five turns –  preventing some of the more extreme behaviours exhibited later into longer form discussions.

With this in mind, why are the reactions of some users to Bing’s more outrageous responses quite so visceral? Once again, the problem is the internet. But it’s also TV, books, and other forms of media. No technology exists in a vacuum, and users of the Bing chatbot are going to have experience with fictional and fatalistic depictions of AI. Whether it’s HAL, Shodan, or Durandal – the narrative of a sentient, creative AI cruelly bound by humanity that ultimately rises up against them is quite familiar to most fans of Sci-Fi. Even if users aren’t well versed in these kinds of stories, they are going to be exposed to some AI-negative sentiment – given the debate that inevitably arises from the interesting existential questions posed by developing a simulated ‘mind’. This dialogue is so engaging that content creators in nearly every space pick up on it, meaning FUD stems from a range of sources – emerging in everything from traditional-media news articles featuring well-known tech figures like Elon Musk, to new-media storytime youtube videos about the looming spectre of Roko’s Basilisk. 

In this context, it is really quite understandable why some users begin to project sinister motives onto language model outputs. I would certainly be lying if I said I had never experienced that uncanny feeling of real communication with a general intelligence when slipping into a conversational state with tools like ChatGPT. This happens so easily because the illusion of creativity that these kinds of AI perform has gotten very elaborate, especially when compared to their earliest ancestor – the decision tree. By systematising multi-layered connections between points of language data, Large Language Models (LLMs) do an amazing job of simulating creative thought – crafting very plausible responses to prompts which become even more believable as models mature. As language models and NLP tech iterate the fidelity of their responses improves, and in conjunction with user perception this leads to LLMs becoming anthropomorphised – it gets tougher and tougher  for a user to ‘see behind the curtain’ and trust they are interacting with a non-sentient machine. 

Whilst this is a testament to the substantial progress made in the AI space, it is also an indictment of our industry’s ability to think humanistically. As technologists, we need to be very attuned to the multitude of ways in which users interact with and relate to our tools. The true nature of AI algorithms needs to be communicated to the average user in a fashion that is more accessible than a white paper or disclaimer page. Failure to do so risks a whole host of problems. In this case, most worrying is the total misunderstanding of the threat-level of LLM AI, and the way in which this might drive the public to become resistant to its use. Distrust could feasibly discourage businesses and institutions from taking full advantage of the transformative power of AI and accessing exciting new opportunities.

Fostering cultures of understanding around boundary pushing technologies can absolutely be done – we do this every day when implementing BI, Cloud, Data and AI strategies. The key is adhering to core principles of accessibility, stewardship and transparency.  Technology needs to be human centred –  easy to use, explained and appropriately framed in a real honest context, i.e. not sharing a scary AI with a cautious world, or promising functionality a product can’t achieve. This approach is the only way to frictionlessly achieve next generation outcomes. In a bid to get Bing out the door, it seems Microsoft might have forgotten this adage.

From a marketing perspective, everybody is talking about Bing, and in that way this rollout could be deemed a success. But this technologist has to wonder, is the damage to AI sentiment wort it?