Pith. sign in

REVIEW 1 cited by

Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2002.04087 v2 pith:XWGQQBAI submitted 2020-02-10 cs.HC cs.AI

classification cs.HCcs.AI
keywords humancontrolcomputerhighlevelsincreaseperformanceartificial
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) framework clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The methods of HCAI are more likely to produce designs that are Reliable, Safe & Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 14 citations worldwide. Full citation record

  1. How Managers Perceive AI-Assisted Conversational Training for Workplace Communication

    cs.HC 2025-05 conditional novelty 6.0 of 10

    Managers view AI-assisted role-play as useful low-stakes practice for workplace conversations, provided it offers customizable scenarios, actionable feedback, and human-AI teaming.

Pith tools