"So, Tell Me What Users Want, What They Really, Really Want!"
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Abstract (arXiv)
Equating users' true needs and desires with behavioural measures of 'engagement' is problematic. However, good metrics of 'true preferences' are difficult to define, as cognitive biases make people's preferences change with context and exhibit inconsistencies over time. Yet, HCI research often glosses over the philosophical and theoretical depth of what it means to infer what users really want. In this paper, we present an alternative yet very real discussion of this issue, via a fictive dialogue between senior executives in a tech company aimed at helping people live the life they `really' want to live. How will the designers settle on a metric for their product to optimise?
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Mar 2018.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.
3 papers.
- 2023Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systemscited by 7
- 2024System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processescited by 2
- 2026Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMscited by 1
- 2026Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMs22 Apr 2026
- 2024System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes29 May 2024
- 2023Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems27 May 2023