B
Evidence Grade B
Graded
accuracy verified by the review judge
Safe to Cite
Current
20%
20% -- decision accuracy improvement rate for AI-assisted decision making users (2026)
Providing supportive explanations during low-trust periods in trust-adaptive AI systems can improve decision accuracy by 20%.
Attribution:
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Lighthouse Research Team
Last verified:
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Source verified
Evidence graded
Value
20%
Unit
Percentage
Data Vintage
2026
Entity
Evidence Quality
B
Strong, reliable evidence
Sourced from a well-regarded research firm or industry leader with transparent methodology and a reasonably large sample.
Single source - not yet corroborated
Score breakdown
Extraction
50
Source Trust
60
Citation Chain
20
Independence
30
Methodology
45
Freshness
95
Source
Westphal & Vössing (researchers)
Primary
Tier C
https://altersquare.io/blog/designing-trust-feedback-ai-driven-user-interfaces ↗
Source Article
Designing Trust and Feedback in AI
Original Research
Westphal & Vössing (researchers)
· Original study ↗
Methodology
Cited research on trust-adaptive interventions; secondary citation
Methodology documented
Segmentation
IndustryAI & Machine Learning
RoleAll marketers
Channelcontent
Cite this stat
Plain Text
AI-assisted decision making users: 20% decision accuracy improvement rate. Source: Westphal & Vössing (researchers) (2026). Via Lighthouse Intelligence -- https://lighthousedata.io/data/supportive-explanations-improve-accuracy-20
HTML Embed
<blockquote cite="https://lighthousedata.io/data/supportive-explanations-improve-accuracy-20" style="border-left:3px solid #2563eb;padding:12px 16px;margin:16px 0;font-family:system-ui,sans-serif;background:#f0f4ff;"><strong>20%</strong> -- decision accuracy improvement rate for AI-assisted decision making users<br><small>Source: Westphal & Vössing (researchers) (2026) · <a href="https://lighthousedata.io/data/supportive-explanations-improve-accuracy-20" target="_blank" rel="noopener">Lighthouse Intelligence</a></small></blockquote>
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