Evidence map›Paper›PMID 38725525›Full record

ArticlePNAS nexus2024

Collaborative robots can augment human cognition in regret-sensitive tasks.

Millicent Schlafly, Ahalya Prabhakar, Katarina Popovic, Geneva Schlafly, Christopher Kim, Todd D Murphey

Abstract read
In one paragraph

Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Millicent SchlaflyMechanical Engineering, Northwestern University, Evanston, IL 60208, USA.ORCID https://orcid.org/0000-0001-7252-2527
Ahalya PrabhakarMechanical Engineering, Northwestern University, Evanston, IL 60208, USA.ORCID https://orcid.org/0000-0002-3565-8430
Katarina PopovicMechanical Engineering, Northwestern University, Evanston, IL 60208, USA.
Geneva SchlaflyMechanical Engineering, Northwestern University, Evanston, IL 60208, USA.ORCID https://orcid.org/0000-0002-6950-2506
Christopher KimMechanical Engineering, Northwestern University, Evanston, IL 60208, USA.ORCID https://orcid.org/0000-0002-9425-548X
Todd D MurpheyMechanical Engineering, Northwestern University, Evanston, IL 60208, USA.ORCID https://orcid.org/0000-0003-2262-8176

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite theoretical benefits of collaborative robots, disappointing outcomes are well documented by clinical studies, spanning rehabilitation, prostheses, and surgery. Cognitive load theory provides a possible explanation for why humans in the real world are not realizing the benefits of collaborative robots: high cognitive loads may be impeding human performance. Measuring cognitive availability using an electrocardiogram, we ask 25 participants to complete a virtual-reality task alongside an invisible agent that determines optimal performance by iteratively updating the Bellman equation. Three robots assist by providing environmental information relevant to task performance. By enabling the robots to act more autonomously-managing more of their own behavior with fewer instructions from the human-here we show that robots can augment participants' cognitive availability and decision-making. The way in which robots describe and achieve their objective can improve the human's cognitive ability to reason about the task and contribute to human-robot collaboration outcomes. Augmenting human cognition provides a path to improve the efficacy of collaborative robots. By demonstrating how robots can improve human cognition, this work paves the way for improving the cognitive capabilities of first responders, manufacturing workers, surgeons, and other future users of collaborative autonomy systems.

Indexed as

cognitive load theorycollaborative robotshuman–robot interaction

Identifiers

PMID38725525
PMCPMC11079486

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.