{"id":16873,"date":"2024-04-18T12:11:04","date_gmt":"2024-04-18T10:11:04","guid":{"rendered":"https:\/\/www.centigrade.de\/?post_type=blog&p=16873"},"modified":"2024-05-02T13:27:17","modified_gmt":"2024-05-02T11:27:17","slug":"highs-and-lows-of-ai-driven-persona-agents","status":"publish","type":"blog","link":"https:\/\/www.centigrade.de\/en\/blog\/highs-and-lows-of-ai-driven-persona-agents\/","title":{"rendered":"AI Personas: Empathy-Amplifier or false pretences?"},"content":{"rendered":"

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Unlike Amazon Echo and Meta, ChatGPT is highly disruptive. But why is that? ChatGPT was the fastest to reach 100 million users and has no dependencies on other technologies. ChatGPT has also offered surprisingly little \u201cethical slippery slope\u201d so far. But the main reason, according to Sam Altman himself, seems to be ChatGPT’s fantastic UX. Good news for all UX professionals.<\/p>\n

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\u201eIf I had to choose a point in time when AI became truly disruptive, I would choose the release of ChatGPT. However, it wasn’t the underlying AI models that made the difference, but the user-friendliness of the application!<\/span>\u201c \u2013 <\/span><\/strong>Sam Altman, CEO OpenAI, Lex Fridman Podcast<\/span><\/p><\/blockquote>\n

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Questioning the Old<\/h2>\n

Looking at the Generative AI wave, we live in disruptive times and must consequently rethink long-unquestioned concepts. This includes established UX methods that have been guiding us well through the product development jungle for years. One of these methods to question is the \u201cpersona\u201d method. The hypothesis of the method is that an AI-generated fictional character may allow us to put ourselves into the shoes of the users and with that feel increased empathy for their pains and gains. A persona is and was, primarily, a communication artifact that elevates the team to a common foundation\u2014if the persona enables all team members to adopt its perspective, then all team members will automatically share that very same perspective. This may sound trivial, but it’s a noteworthy effect because channeling discussions and fostering a more united pursuit of a common goal will ultimately lead to better work results.<\/p>\n

Critique of the Persona Method<\/h2>\n

Whether the persona method has worked well so far, I leave to each individual, as I don’t think it can be answered per se. However, there has always been a certain scepticism towards the method during my entire 20+ year career. Especially algorithmically thinking software engineers usually prefer quantitative analyses based on “hard data” instead of settling upon seemingly arbitrarily chosen characteristics of people who don’t even really exist at the end of the day. The funny part of this? Well, in my view, it remains to be clarified whether some software engineers might have more empathy for data than for people \ud83d\ude42<\/p>\n

\"Skeptischer<\/p>\n

Honestly, I assume that the aversion against personas results less from a general lack of empathy but more from the diffuse yet correct feeling of being confronted with only parts of the truth. If a persona is defined as 32 years old and female, a software engineer might rightly wonder: “Would a 28-year-old male user fail using the software just because he has a Y chromosome? Would the user just need to age four years to then understand the software?\u201d Of course not.<\/p>\n

Authority and Fallibility of UX Research<\/h2>\n

Fortunately, such questions will not make a holistically and systemically thinking person lose its faith in the method, as functional clarity and algorithmic processing are not the core reasoning behind empathy and perspective taking. Nonetheless, the uneasy feeling remains: at some point, a UX research<\/a> professional (or a team thereof) made the decision to distill a certain age and gender from a pool of many questionnaires, many ages and many genders to finally come up with a fixed set of \u201cslices\u201d in the shape of one or more personas. In this case, we encounter a much deeper issue: all design decisions based on a persona ultimately rely on the non-calculable authority and skillset of just a few UX research professionals… who are psychologists, yes. But after all, they are still fallible, if I’m not mistaken.<\/p>\n

AI is fallible, too<\/h2>\n

To connect back to Generative AI, especially Large Language Models (LLMs): actually, there’s no longer a need for user researchers to manually generate personas from a set of user research data with the risk of potentially making mistakes along the way. With the help of Generative AI, we can arrive at a collection of personas without detouring through low-level UX research work. As I dryly noted in my blog post <\/a>last year: humans are fallible, and so is AI. But: the fallibility of AI, at least in this case, is at least not<\/em> resulting from opinion biases or complexity overload.<\/p>\n

A UX researcher who implicitly wishes to advocate for a more sustainable world will inevitably and perhaps even unconsciously emphasize those persona traits that he or she regards as particularly important for a sustainable design decision. The persona is then biased and “opinionated\u201d.<\/p>\n

But who guarantees that AI-generated personas aren’t biased and “opinionated”? I think, in the end, it can be boiled down to: “Prompts and grounding data make the music,” and a prompt or grounding data set that introduces a tendency towards, for instance, sustainability in the input will naturally also consider or even emphasize these topics in the output.<\/p>\n

The design leadership experiment<\/h2>\n

Autumn 2023, me and my team at Centigrade had the opportunity to conduct a highly exciting experiment. We were invited by BOSCH\u2019s design leadership team to spend an entire afternoon giving a workshop on the intersection of Generative AI and Design<\/a> to their in-house design leadership team. We leveraged a software tool capable of generating usable personas via AI, namely LeanScope AI<\/a>. Together with our Centigrade partner NUILAND<\/a>, we built a cabinet similar to a ticketing machine and our Centigrade developers modded a kiosk version of the software. Instead of tickets, however, this machine printed out AI-generated persona posters. Then, we divided the designers into 6 groups of 10 participants each. Each group was allowed to generate its own persona to rethink a BOSCH product of their choice in light of the GenAI wave.<\/p>\n

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And now for the twist: what the participants did not know was that we had not only visually transformed LeanScope into a kiosk mode but we had also modified the prompts responsible for generating the personas. We overrode the master prompt so that, no matter what persona role was requested by the user, the generated output persona was highly biased towards sustainability. For instance, if you entered “electrician” as a role, then the resulting persona was frustrated about having to throw away old cables that were still usable. Funnily, if you entered “vampire\u201d, the resulting persona was frustrated that he wants to coexist peacefully with all creatures in the world, but unfortunately, his urge for blood often gets the upper hand. After all, a sustainable vampire does not drink more blood than necessary to survive. Comforting to know.<\/p>\n