From peer review to performance management, feedback systems shape what gets corrected, what gets ignored, and what is allowed to persist. When those systems weaken – or are quietly automated – the consequences extend far beyond individual reactions.
Providing feedback is often described as a ‘soft’ skill that good leaders and good reviewers should master. In reality, it is neither soft nor optional. Across contexts – whether in research or organisational life – feedback functions as a core quality-assurance mechanism. It underpins trust, supports psychological safety [1], and directly shapes performance, learning and progress. Without it, neither teams nor bodies of knowledge can reliably improve.
This is as true in research as it is in management. Peer review and workplace feedback sit in different professional worlds, yet they are built on strikingly similar foundations. Both exist to improve quality, surface risk, correct errors, and support progress. Both rely on trust – not just interpersonal trust but trust in the process itself. And in both contexts, when feedback fails, the damage extends well beyond hurt feelings or missed opportunities.
This feedback vulnerability is not merely anecdotal. Decades of research show that feedback systems can either strengthen performance or actively undermine it, depending on how they are designed and applied. Kluger suggested that ‘Feedback interventions do not uniformly improve performance; their effects depend on how attention is directed within the task and system’. [2]
Delivered incorrectly, feedback undermines confidence in outcomes, distorts decision-making, and erodes psychological safety. Seen this way, feedback is not an optional add-on to good practice; it is the infrastructure that allows good practice to exist at all. It is ‘one of the most powerful influences on learning and achievement’ [3].
Feedback as quality control, not commentary
At its best, feedback is an active form of quality assurance. In research, peer review exists to test the robustness of methods, the coherence of argument, and the credibility of conclusions before work enters the scholarly record. In management, feedback serves a parallel function: it checks assumptions, identifies weaknesses, and ensures that decisions and outputs are fit for purpose before they are scaled.
Crucially, neither system is designed to be comfortable, and both should slow learning in the short term while improving long-term performance and skill transfer [4].
This means that, inevitably, good feedback introduces a certain amount of friction because it slows momentum long enough to ask whether progress is genuinely meaningful or merely procedural. Such a pause matters, as without it, work can appear to advance while quietly accumulating errors, ambiguity, or untested assumptions. When feedback functions properly, it challenges the work rather than the person, creating pressure for improvement without destabilising confidence, and correction without humiliation.
Problems arise when feedback is reframed as commentary rather than scrutiny. For example, in workplaces, this often looks like vague praise, softened criticism, or annual reviews that avoid difficult conversations in favour of reassurance. In peer review, it can appear as cursory reports, box-ticking, or critiques that focus on stylistic preference rather than substantive validity. In both cases, the system still exists on paper, but it no longer performs its core function.
Trust is built through process, not tone
Much of the recent discussion around feedback focuses on tone, on being kind, supportive, or constructive. Undoubtedly, tone matters, but it is not the primary driver of trust. Trust emerges when people believe that a process is fair, consistent, and meaningful, even when its outcomes are challenging. People are more likely to accept unfavourable outcomes when they believe the process was fair, transparent, and consistently applied [5–6].
In research, authors accept critical peer review when they believe reviewers are competent, independent, and genuinely engaging with the work. In management, staff are more likely to accept difficult feedback when they trust that expectations are clear, standards are applied consistently, and decisions are not arbitrary or performative.
When trust is absent, feedback – however politely phrased – is experienced as threatening to status or competence rather than as information for improvement. We inevitably begin to second-guess motives, withhold information, or disengage altogether. Psychological safety, so often invoked in workplace discussions, cannot exist where feedback feels unpredictable or weaponised. The same holds true in academic publishing, where opaque editorial decisions or inconsistent peer review standards can discourage risk-taking and innovation.
Yet trust does not require an agreement of opinion; it requires confidence that disagreement is handled with intellectual honesty rather than subjective judgement.
When feedback works well
When feedback systems function as intended, their benefits are cumulative. In research, rigorous peer review strengthens the literature, filters error before publication, and builds confidence in scholarly dialogue. Authors may not enjoy the process, but they recognise its value – and often produce stronger work as a result.
In management contexts, effective feedback supports clarity, alignment, and professional growth. It enables teams to adjust course early, reduces costly mistakes, and fosters a shared understanding of standards. Over time, this kind of feedback culture supports resilience: people are better equipped to handle change because they are accustomed to scrutiny and revision.
What links these outcomes is not positivity, but purpose. Feedback works when it is clearly connected to improvement, and when those receiving it understand how to act on it. Actionability matters. Feedback that identifies problems without offering a path forward may feel thorough, but it ultimately stalls progress.
When feedback fails
The costs of poor feedback are less immediately visible, but no less serious. In research, inadequate peer review allows flawed work to enter the record, where it may influence policy, practice, or further research before errors are identified. Conversely, excessively hostile or unfocused reviews can suppress novel ideas, reinforce orthodoxy, and disproportionately disadvantage certain voices.
In workplaces, weak feedback systems produce similar distortions. Performance issues linger unaddressed until they escalate. Decisions are made on incomplete information. High performers become frustrated by a lack of recognition, while underperformance is tolerated out of avoidance rather than strategy. Over time, trust erodes – not because feedback was harsh, but because it was absent or incoherent.
Perhaps most damaging is feedback that exists in name only. Annual appraisals that change nothing, peer reviews that are never meaningfully engaged with, and consultation processes that have no visible impact all teach the same lesson: input is invited, but not valued. Once that lesson is learned, disengagement is rational.
Shared pressures, shared lessons
Both peer review and workplace feedback systems are currently under strain. In academia, rising submission volumes, reviewer fatigue, and the growing presence of AI tools are testing the limits of traditional peer review models. In organisations, rapid change, remote working, and performance pressures are exposing the weaknesses of feedback processes that were never designed for complexity or speed.
These pressures make it tempting to streamline, automate, or minimise feedback. Yet doing so risks hollowing out the very mechanisms that maintain quality and trust. Efficiency gained at the expense of scrutiny is rarely a good trade-off.
The lesson across both contexts is the same: feedback must be treated as core infrastructure. It requires investment, clear standards, and ongoing maintenance. It also requires humility – an acceptance that no system is perfect, and that feedback processes themselves must be open to review.
One reason feedback systems struggle under pressure is that they are often asked to perform incompatible functions simultaneously. In both organisations and academia, feedback is expected to correct errors, support development, assess competence, and justify decisions. These aims are not always aligned. Developmental feedback requires openness and trust; evaluative feedback introduces risk and consequence. When systems fail to distinguish clearly between these purposes, feedback becomes confusing rather than clarifying.
The Feedback–AI Loop
Trust in feedback does not emerge simply because feedback is frequent or well-intentioned. It develops when people learn, over time, that feedback carries reliable engagement – that it reflects attention, judgement, and an understanding of context.
This is where trust is increasingly tested.
As automated and AI-assisted tools are used to generate feedback at scale, the form of feedback can appear intact while its substance continues to thin. Comments may sound fluent and authoritative, yet be untethered from genuine engagement with the work itself.
Research on algorithmic decision-making and automated evaluation shows that people are sensitive to this distinction: feedback perceived as generic or automated is consistently rated as less credible and less useful, even when it is linguistically polished [7]. When feedback is delivered without evidence of human thought – without specificity, prioritisation, or clear linkage to decisions – it begins to feel procedural rather than considered.
In such environments, people learn quickly to discount feedback, not because it is critical, but because it lacks discernible intent. The risk is not that AI is used, but that feedback loses its status as meaningful information and becomes background noise. When that happens, trust erodes quietly, and feedback ceases to function as a guide for improvement.
For authors, this loss of human engagement and thought creates a very human consequence. Submitting months or years of careful research only to receive feedback that appears automated or generic can feel dismissive, even invalidating – not because criticism is unwelcome, but because the work itself does not appear to have been meaningfully read. Studies of algorithmic judgement show that people are markedly less accepting of decisions or evaluations when they believe human effort has been replaced rather than supported, particularly in contexts involving expertise, identity, or high personal investment [8]. In peer review, where credibility and scholarly trust are foundational, that perception alone is enough to weaken confidence in the system, regardless of the technical quality of the feedback itself.
Our ethical responsibility
Ultimately, feedback is not just a practical tool; it is an ethical responsibility. In research, it reflects a commitment to the integrity of the scholarly record and to the communities that rely on it. In management, it reflects a commitment to fairness, development, and responsible decision-making.
Avoiding feedback may feel kind in the moment, but it is rarely kind in the long term. Equally, delivering feedback without care for structure, clarity, or consequence is not rigour, it is negligence. The challenge is not to make feedback painless, but to make it purposeful, transparent, and trustworthy.
When feedback systems work, they enable progress that is both confident and accountable. When they fail, progress becomes illusory – busy, but brittle. In both research and management, the difference lies not in individual skill alone, but in how seriously feedback is designed, supported, and valued.
Feedback In Practice at PA EDitorial
As PA EDitorial’s CEO, Lizi Dawes, notes, ‘fostering a healthy feedback culture means being willing to have difficult conversations in service of quality, while making it clear that scrutiny is about the work, never the person’.
As an editorial organisation, feedback is not an abstract concept for us. We spend a great deal of time thinking about how feedback is given, received, and acted on – both within our own team and across the journals and partners we work with. We not only recognise that feedback is rarely comfortable, but that it must always be considered, proportionate, and grounded in genuine engagement with the work. Like many organisations, PA EDitorial draws on a range of thinking to support this, including Kim Scott’s Radical Candor [9], which offers a useful lens on balancing honesty with care.
No single framework provides all the answers, but the underlying principle is consistent: feedback only builds trust when it is real, intentional, and taken seriously.
SOURCES
[1] Edmondson, A. (1999). ‘Psychological safety and learning behavior in work teams’. Administrative Science Quarterly, 44(2), pp. 350–383. https://doi.org/10.2307/2666999
[2] Kluger, A. N. and DeNisi, A. (1996). ‘The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory’. Psychological Bulletin, 119(2), pp. 254–284. https://doi.org/10.1037/0033-2909.119.2.254
[3] Hattie, J. and Timperley, H. (2007). ‘The power of feedback’. Review of Educational Research, 77(1), pp. 81–112. https://doi.org/10.3102/003465430298487
[4] Bjork, R. A. (1994). ‘Memory and metamemory considerations in the training of human beings’. In Metacognition: Knowing about knowing. MIT Press.
[5] Tyler, T. R. (1990). Why People Obey the Law. Yale University Press.
[6] Tyler, T. R. (2006). Why People Cooperate. Princeton University Press.
[7] Binns, R., Van Kleek, M., Veale, M., Lyngs, U., Zhao, J. and Shadbolt, N. (2018). ‘“It’s reducing a human being to a percentage”: Perceptions of justice in algorithmic decisions’. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM. https://doi.org/10.1145/3173574.3173951
[8] Dietvorst, B. J., Simmons, J. P. and Massey, C. (2015). ‘Algorithm aversion: People erroneously avoid algorithms after seeing them err’. Journal of Experimental Psychology: General, 144(1), pp. 114–126. https://doi.org/10.1037/xge0000033
[9] Scott, K. (2017). Radical Candor: Be a Kick-Ass Boss Without Losing Your Humanity. London: Pan Macmillan.