Services

Conversation · Response quality · Human judgment

Human–AI interaction & communication

An AI response can read smoothly and still leave someone with the wrong impression. It may miss the question, lose an important condition or sound more certain than the available information allows.

I offer review of AI conversations and responses from a language and communication perspective. The focus is on what the response communicates, how it fits the exchange and what the person using it is likely to understand.

What the review considers

• Relevance and context: does the response address the actual request, carry forward important details and recognise when clarification is needed?
• Clarity and usefulness: can the reader follow the answer and understand what, if anything, to do next?
• Tone and relationship: does the language suit the situation without becoming dismissive, intrusive, flattering or unnecessarily formal?
• Claims and expectations: does the response distinguish what is known from what is inferred, and describe its capabilities accurately?
• Consistency across the exchange: do later answers respect earlier constraints, terminology and relevant context?

Feedback a team can use

We agree a defined sample and assessment criteria around the product, audience and intended use. The deliverable can include annotated responses, suggested wording, explanations of recurring issues and priorities for revision.

Where an answer makes a factual claim, checking it requires a suitable reference or subject expert. Unresolved questions are recorded for the relevant team to assess. Findings from a sample describe that sample.

Human understanding at the centre

People bring expectations, concerns and assumptions to a conversation. A useful review considers those alongside the literal content of the answer.

My interests in psychology and philosophy inform this attention to interpretation and human judgment. The service itself has a defined communication scope, with product decisions and specialist validation remaining with the responsible team.

Scope the work

Share the product’s purpose, intended users, languages, example conversations and any existing rubric or reference material. We can then agree what needs to be evaluated and how the findings should be delivered.

For source-to-target Danish checks, terminology and machine-translation review, see AI & linguistic quality in Danish. For original writing and editorial development, see Communication & meaning.