Author: anacanhoto

March 2025 round-up

March was a good month. Sure, hay fever is annoying and  it wasn’t fun to deal with a trapped nerve. But there were also many highlights such as running in nice weather, kicking off the SeNSS training series on GenAI in research with my AI literacy session, or joining a panel of AI experts, to discuss the … Continue reading March 2025 round-up

Helpful resources for generative AI newbies in academia

If you are an academic (including a PhD student) curious about the potential of generative AI (GenAI) in a university context, but not sure where to start, here are some helpful resources. About the technology Research shows that understanding GenAIs’ strengths and weaknesses is crucial to enable a critical approach to its use. So, my first set … Continue reading Helpful resources for generative AI newbies in academia

Conversations with Chat GPT: Convention over linguistic rules

While I warmly encourage everyone to get familiar with generative AI, I often suggest that they use it mostly for purposes where it doesn’t matter if the answer is correct or not. If one must use it in a context where accuracy matters, then I suggest using it only when we know the answer and can … Continue reading Conversations with Chat GPT: Convention over linguistic rules

Introduction to generative AI for PhD students (slides + video)

Earlier this month, I ran a brief “introduction to generative AI” session for PhD students and post-docs enrolled in the SeNSS/ SENSS doctoral training partnership.  Here are the slides used in the session, and the video recording. https://www.slideshare.net/slideshow/introduction-to-generative-ai-for-phd-students/276734708 Introduction to generative AI for PhD students from Ana Canhoto The session drew on my socio-technical framework for … Continue reading Introduction to generative AI for PhD students (slides + video)

Why Women Must Engage with Generative AI (and How to Get Started)

Study after study after study shows that fewer women than men are using generative AI.  Image source The reasons for this AI gender gap are numerous and, to be frank, are not new. Some of the causes mentioned in the emerging literature are: Lack of exposure to generative AI in the workplace: There is still a difference in … Continue reading Why Women Must Engage with Generative AI (and How to Get Started)

Outline for my AI literacy training session, for early career researchers

The development of AI skills (and generative AI, as part of that) is likely to have a major impact in the employability and professional success of early career graduates, both directly (i.e., in the form of demonstrated ability to use these tools) and indirectly (e.g., through impact on productivity).  As such, I am developing an … Continue reading Outline for my AI literacy training session, for early career researchers

When Do Customers Trust AI-recommendations?

The question of when customers will welcome vs reject an AI recommendation is important from both a practical and a conceptual perspective. From the practical perspective, the answer to this question will inform investment in AI recommendation systems (where to invest, risks faced, AI-system features…). From a conceptual one, the answer reveals the boundary conditions … Continue reading When Do Customers Trust AI-recommendations?

New paper: Forced vs Voluntary Chatbot Use: How It Shapes Customer Satisfaction and Blame

As chatbots become an integral part of customer service, mistakes remain inevitable. Whether it’s a failure to understand the customer’s intent or an error in executing an order, such failures raise a key question: Who do customers blame— themselves or the company? Blame attribution shapes customers’ subsequent behaviour. For instance, if I think that I received … Continue reading New paper: Forced vs Voluntary Chatbot Use: How It Shapes Customer Satisfaction and Blame