Evidence map›Paper›PMID 38533466›Full record

ArticleFrontiers in artificial intelligence2024

tachAId-An interactive tool supporting the design of human-centered AI solutions.

Max Bauroth, Pavlos Rath-Manakidis, Valentin Langholf, Laurenz Wiskott, Tobias Glasmachers

Open access · goldAbstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
3.7field-weighted citation impact, top 7% of its field
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

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 1 institution in 1 country.

Max Bauroth *Faculty of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany.
Pavlos Rath-Manakidis *Faculty of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany.
Valentin LangholfInstitute of Work Science, Ruhr University Bochum, Bochum, Germany.
Laurenz WiskottFaculty of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany.
Tobias GlasmachersFaculty of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany.
Ruhr University Bochum · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In an era where Artificial Intelligence (AI) integration into business processes is crucial for maintaining competitiveness, there is a growing need for structured guidance on designing AI solutions that align with human needs. To this end, we present "technical assistance concerning human-centered AI development" (tachAId), an interactive advisory tool which comprehensively guides AI developers and decision makers in navigating the machine learning lifecycle with a focus on human-centered design. tachAId motivates and presents concrete technical advice to ensure human-centeredness across the phases of AI development. The tool's effectiveness is evaluated through a catalog of criteria for human-centered AI in the form of relevant challenges and goals, derived from existing methodologies and guidelines. Lastly, tachAId and one other comparable advisory tool were examined to determine their adherence to these criteria in order to provide an overview of the human-centered aspects covered by these tools and to allow interested parties to quickly assess whether the tools meet their needs.

Indexed as

artificial intelligencehuman-AI interaction (HAII)human-centered AIhuman-centered designhuman-centered design goalstachAId

Identifiers

PMID38533466
PMCPMC10963619
OpenAlexW4392714294

What OpenQuestion 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 OpenQuestion graph.