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arxiv: 2601.11884 · v2 · submitted 2026-01-17 · 💻 cs.HC

AI-Mediated Hiring and the Job Search of Blind and Low-Vision Individuals

Kashif Imteyaz , Qiushi (Anya) Liang , Yakov Bart , Maitraye Das , Saiph Savage This is my paper

Pith reviewed 2026-05-16 13:43 UTC · model grok-4.3

classification 💻 cs.HC
keywords AI hiringblind and low-visionjob searchdisabilitystrategic refusalpeer networksinterdependencealgorithmic screening
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The pith

AI hiring systems misrepresent the professional identities of blind and low-vision job seekers, prompting strategic workarounds and community support.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines how blind and low-vision people experience AI-driven resume screening and hiring platforms. Interviews with 17 participants show that these systems often distort their work histories and produce impersonal or inaccessible interactions. In response, job seekers build their own bypass tools, share knowledge through peer networks, and sometimes opt out of AI processes entirely to maintain control. The authors frame these actions as evidence that job search for this group is an interdependent activity shaped by community ties rather than a solitary task. This leads to recommendations for AI tools that incorporate disability perspectives and support mutual aid.

Core claim

AI hiring systems misrepresented professional identities of blind and low-vision job seekers and created dehumanizing interactions. Participants responded with strategic counter-navigation to bypass screening, peer networks to share AI literacy, and strategic refusal to avoid certain systems. Job search for BLV individuals is therefore an interdependent process rather than an individualistic one.

What carries the argument

Strategic counter-navigation combined with the interdependence framework that treats job search as a collective activity supported by peer networks.

Load-bearing premise

The experiences described by the 17 self-selected interviewees reflect the typical barriers and responses of blind and low-vision job seekers overall.

What would settle it

A larger study of blind and low-vision job seekers that finds most do not encounter identity misrepresentation from AI systems or do not rely on peer networks and refusal tactics.

Figures

Figures reproduced from arXiv: 2601.11884 by Kashif Imteyaz, Maitraye Das, Qiushi (Anya) Liang, Saiph Savage, Yakov Bart.

Figure 1
Figure 1. Figure 1: Conceptual models of BLV job search: (A) Independence and (B) Interdependence views. [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
read the original abstract

Blind and low-vision (BLV) individuals face high unemployment rates. The job search is becoming harder as more employers use AI-driven systems to screen resumes before a human ever sees them. Such AI systems could inadvertently further disadvantage BLV job seekers, introducing additional barriers to an already difficult process. We lack understanding of BLV job seekers' experiences in today's AI-driven hiring ecosystem. Without such understanding, we risk designing technologies that create new systemic barriers for BLV job seekers rather than providing support. To this end, we conducted interviews with 17 BLV job seekers and analyzed their experiences with AI-powered hiring systems. We found that AI hiring systems misrepresented their professional identities and created dehumanizing interactions. To level the playing field, BLV job seekers used strategic counter-navigation: they deployed their own tools to bypass algorithmic screening and built peer networks to share AI literacy. They also practiced 'strategic refusal', choosing to avoid certain AI systems to regain their agency. Unlike prior work that frames job search as an individualistic activity, or one focused on being compliant with employer needs, we use the interdependence framework to argue that for BLV people, job search is an interdependent process. We offer design recommendations for AI-mediated tools that center disability perspectives and support interdependencies in job search.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The paper reports findings from semi-structured interviews with 17 blind and low-vision (BLV) job seekers. It claims that AI-mediated hiring systems frequently misrepresent BLV professional identities and produce dehumanizing interactions; participants respond via strategic counter-navigation (deploying personal tools to bypass screening), peer-network sharing of AI literacy, and strategic refusal of certain platforms. The authors contrast this with prior individualistic or compliance-focused framings of job search and instead apply an interdependence framework from disability research to argue that BLV job search is inherently interdependent, offering design recommendations for AI tools that center disability perspectives.

Significance. If the thematic findings are robust, the work makes a meaningful contribution to HCI and accessibility by documenting concrete mechanisms through which AI hiring tools disadvantage BLV applicants and by demonstrating the utility of the interdependence lens for technology design. Explicit credit is due for grounding the analysis in an established external framework rather than ad-hoc constructs and for translating participant strategies into actionable design recommendations.

major comments (2)
  1. [Methods] Methods section: the description of recruitment (via disability organizations and social media) and thematic analysis provides no information on interview protocol, coding procedures, saturation criteria, member-checking, or steps to mitigate researcher bias. Because the central claims about misrepresentation, dehumanizing interactions, and the necessity of interdependent strategies rest entirely on this analysis, the absence of these details prevents evaluation of how reliably the themes map to the data.
  2. [Results/Discussion] Results and Discussion: the argument that job search for BLV individuals is an interdependent process (rather than individualistic) is derived from reported strategies in a self-selected sample of 17 participants. No counter-examples, negative cases, or triangulation with objective measures (e.g., resume audit data) are presented; without addressing how selection via advocacy channels may over-represent negative AI encounters, the load-bearing shift to the interdependence framing lacks sufficient grounding.
minor comments (1)
  1. [Abstract] Abstract: the opening sentence on unemployment rates would benefit from a specific citation to recent statistics for precision.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for their thoughtful and constructive review. We have addressed the major comments by expanding methodological transparency and strengthening the discussion of sample limitations and the grounding of the interdependence framework. Below we respond point by point.

read point-by-point responses

  1. Referee: [Methods] Methods section: the description of recruitment (via disability organizations and social media) and thematic analysis provides no information on interview protocol, coding procedures, saturation criteria, member-checking, or steps to mitigate researcher bias. Because the central claims about misrepresentation, dehumanizing interactions, and the necessity of interdependent strategies rest entirely on this analysis, the absence of these details prevents evaluation of how reliably the themes map to the data.

    Authors: We agree that the Methods section requires additional detail to support evaluation of the analysis. In the revised manuscript we will expand the section to include: (1) the semi-structured interview protocol with example questions focused on AI hiring experiences; (2) the thematic analysis procedure, following Braun and Clarke’s six-phase approach with inductive coding and iterative theme refinement through team consensus; (3) assessment of saturation, which occurred after 15 interviews with the final two confirming no new themes; (4) member-checking via sharing of preliminary theme summaries with five participants for feedback and validation; and (5) steps taken to mitigate researcher bias, including reflexive journaling and regular peer debriefing among the research team. These additions will make the mapping from data to themes transparent. revision: yes

  2. Referee: [Results/Discussion] Results and Discussion: the argument that job search for BLV individuals is an interdependent process (rather than individualistic) is derived from reported strategies in a self-selected sample of 17 participants. No counter-examples, negative cases, or triangulation with objective measures (e.g., resume audit data) are presented; without addressing how selection via advocacy channels may over-represent negative AI encounters, the load-bearing shift to the interdependence framing lacks sufficient grounding.

    Authors: We acknowledge the limitations of the self-selected sample recruited through disability organizations and social media, which may over-represent individuals with negative AI encounters or strong advocacy ties. In the revised manuscript we will add an explicit limitations subsection in the Discussion that addresses potential selection bias and its implications for the interdependence framing. We will also incorporate negative cases and counterexamples present in the data (e.g., instances where participants described more individualistic approaches or did not experience identity misrepresentation) to provide balance. The interdependence argument will be further grounded with additional participant quotes that directly link reported strategies (peer networks, personal tools, strategic refusal) to the framework. Triangulation with objective measures such as resume audit studies is not feasible within this qualitative interview study and will be noted as a limitation and direction for future work. revision: partial

standing simulated objections not resolved
  • Triangulation with objective measures (e.g., resume audit data) cannot be added without new data collection outside the scope of revising the current manuscript.

Circularity Check

0 steps flagged

No significant circularity in qualitative empirical study

full rationale

The paper reports thematic analysis of semi-structured interviews with 17 BLV job seekers. Its central claims (AI misrepresentation of identities, dehumanizing interactions, strategic counter-navigation, strategic refusal, and interdependence framing) are presented as emerging directly from coded participant experiences rather than from any equations, fitted parameters, or predictions that reduce to the study's own inputs by construction. The interdependence framework is invoked as an external lens from prior disability research; the text does not indicate that this framework originates in the authors' own prior equations or that the findings are forced by self-citation. No self-definitional, fitted-input, or uniqueness-imported steps appear. The study is therefore self-contained against external benchmarks of interview data and thematic coding.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claims rest on the validity of self-reported interview data and the applicability of the interdependence framework to AI-mediated job search; no free parameters or new entities are introduced.

axioms (1)
  • domain assumption Self-reported experiences of 17 BLV job seekers accurately reflect the typical barriers created by AI hiring systems
    Qualitative studies rely on participant accounts without external corroboration such as logged interaction data.

pith-pipeline@v0.9.0 · 5544 in / 1207 out tokens · 28893 ms · 2026-05-16T13:43:45.522623+00:00 · methodology

discussion (0)

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