AI · Randomized interface-transparency experiments.

How much information? Effects of transparency on trust in an algorithmic interface

CHI. · 2016

Kizilcec, R. F.

Original paper ↗

Summary

Transparency has a non-monotonic effect on trust; framing and amount matter.

For your marketing

Possible founder application

Explain purpose, process, and limits at the right level.

Reported result

What the study found

Transparency has a non-monotonic effect on trust; framing and amount matter.

Research question

What the authors investigated

How does transparency affect algorithmic trust?

Design

Randomized interface-transparency experiments.

Sample and setting

Online users interacting with an algorithmic interface.

Scope and transfer

Limitations to keep in view

Consumer interface and short-term trust outcomes.

Research sources

Publisher abstract/full text supports the reported design, sample, and findings.

Additional research source ↗

Study strength

3.5/5 Abstract-level evidence is useful for framing questions; verify full methods before transfer.

How this was assessed

The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.

Design transparency · 2/2

Based on the reported study design in the retrieved source.

Sample and setting · 1/1

The sample context is stated; a numerical count is preserved only when reported.

Outcome clarity · 1/1

The finding is summarized from publisher or article metadata.

Access for checking · 0.5/1

Only abstract or bibliographic access was confirmed.

Double-blind? The retrieved publisher record does not establish whether participants or outcome assessors were blinded.

Read the paper