← Back to BlogsBlogs

Blog: AI Orientation: webinar recap

AI Orientation in practice: a recap of our webinar

We recently hosted a webinar led by Ben Williams, Chief Scientist at Unseen, on how employers can assess the psychological factors that shape people’s approach to AI, alongside their current AI skills.

AI capability describes what someone knows and can do with AI today. It can be important when a role requires a particular skill from day one, but platform-specific measures may not transfer to other tools, and tests of technical skills can date quickly as technology changes.

AI Orientation offers a broader view. The webinar introduced three related areas:

  • Dispositions and personality: ways of thinking, feeling and behaving.

  • AI-specific motivation and confidence: whether someone sees value in learning, feels able to do so and is willing to invest effort.

  • Attitudes, values and beliefs: what someone trusts about AI, how they view its consequences and which uses they consider acceptable.

    • These areas can help explain why people with similar skills may respond differently to new AI tasks. What they do not do is point to one ideal AI profile, instead, the role should determine which aspects matter.

    Ben then outlined how employers can put AI Orientation into practice: start with job analysis, establish the capabilities needed on entry, identify which aspects of AI Orientation matter for the role, and choose suitable ways to assess them.

    Our latest whitepaper, Beyond AI Literacy: A psychological analysis of why assessing for today’s AI skills is no longer enough, explores this process in more detail, including how existing assessments can be used and where structured interviews or realistic exercises may help.

    Three questions from the discussion

    How can an organisation assess AI Orientation when they have hundreds of roles?

    Ben’s answer was to balance consistency with enough detail to reflect the work:

  • Look for clusters of roles and the requirements they share.

  • Apply more detail where AI use has different or more significant implications.

  • Avoid both a bespoke assessment for every role and treating every role as identical.

    • This is a pragmatic way to decide what can be assessed consistently and where a role needs closer attention, rather than a fixed formula for grouping jobs.

    Can AI Orientation develop after someone is hired?

    One employer asked about development over time and specifically what to do when employee attitudes change, for example if they become more cynical about AI. Ben noted that the right response depends on the organisation and why attitudes have changed. There is no single intervention that will shift every team’s views.

    Personality tends to be more stable, while confidence, motivation and ethical views can change with experience and context. Development conversations can explore what is behind a person’s response. For example, someone who doubts they can learn a new tool might reflect on a time they successfully learned new technology. Someone who sees little value in AI, or objects to a particular use, needs a different discussion.

    What if a candidate objects to AI in selection?

    Ben shared a recent story from an event where a panel of students said they might react negatively to AI in recruitment, including on environmental grounds. Other candidates may welcome AI in selection because they expect a quicker process or believe it could reduce bias.

    Employers should understand whether the concern is about the selection method, a particular tool or AI use in the job, then assess candidates against the actual role requirements using consistent evidence.

    Watch the webinar recording to find out more about AI Orientation

    Share this article: