It is a trope as old as recorded history: older generations criticising the perceived shortcomings of the youth and the degradation of cultural and professional norms. Socrates lamented the youth of Athens for their disrespect and laziness. Every era produces its critics who claim the golden age has passed. Cognitive biases such as ‘rosy retrospection’ predispose us to view the past through a filter of selective memory [1]. Yet our recollections of youthful vigour and professional seriousness may be tinged with the glow of personal ambition and idealism.
However, scepticism toward change should not be dismissed wholesale. Obviously, I would say this as an ageing curmudgeon. And yet, scientific integrity, professional standards, and ethical business practice are not generational preferences, they are the backbone of progress. With a vantage point that spans decades of technological evolution and corporate practice, I feel I have a unique lens to evaluate whether modern trends represent progress or peril. If their decay is real, it should be investigated with the same rigour we apply to any hypothesis.
Before I start, it is worth acknowledging that the perception of declining standards is itself a well-documented psychological phenomenon. The tendency to view the past as superior to the present, what psychologists term ‘declinism’, is remarkably persistent across cultures and eras [2].
Rosy retrospection, describes our tendency to remember past events more favourably than they actually occurred. We forget selectively the frustrations, mediocrities, and ethical lapses of earlier eras while amplifying their virtues. Survivorship bias further distorts our view: we remember the exceptional achievements that have stood the test of time while forgetting the vast majority of mediocre work that has rightly been consigned to obscurity [3]. Shifting baseline syndrome, originally described in ecology, suggests that each generation accepts as normal the conditions they experienced early in life, perceiving any deviation as decline [4]. Availability bias ensures that recent failures and scandals are more cognitively accessible than those from decades past, reinforcing the impression that things are getting worse [5]. These mechanisms operate alongside more general aspects of human cognition, including our tendency to process information through affect-laden heuristics rather than objective analysis [6].
Such psychological mechanisms are not mere academic curiosities. They suggest that the issue of declining standards is, to some extent, a predictable feature of human cognition rather than an objective measure of reality. A rigorous scientist must therefore ask: am I observing genuine degradation, or am I falling prey to the same cognitive biases that have afflicted every generation before me?
In recent years, I have witnessed what appears to be a troubling shift. Projects are too often pressured to meet arbitrary deadlines rather than scientific readiness. The focus on 'speed to market' seems to have superseded 'fit for purpose.' Regulatory capture occasionally serves to exacerbate these issues. The FDA's accelerated approval pathway, intended for urgent therapies, has faced sustained criticism for approving drugs before their clinical benefit is confirmed, with follow-up trials frequently falling behind schedule. A 2022 report from the HHS Office of Inspector General found that, of 278 drug applications granted accelerated approval from 1992 through 2021, 34% of those with incomplete confirmatory trials were past their original planned completion dates, some by more than five years [7]. This laxity mirrors broader corporate governance trends, where short-term gains eclipse long-term accountability..
The rise of contract research organisations (CROs) and increasing outsourcing of critical R&D tasks, while logistically and economically beneficial, has created operational silos and diluted scientific ownership. Junior scientists, disincentivised from challenging data inconsistencies or poorly designed protocols, often nod along to flawed project plans in a climate where speaking up is seen as obstructionist. This is not conjecture, it is an observable pattern reinforced by an avalanche of protocol amendments and operational concerns [8][9].
Perhaps the most insidious trend is not overt misconduct but the gradual erosion of scientific craft. Organisations increasingly reward ‘following processes’ over understanding principles. The proliferation of standard operating procedures, templates, and compliance checklists has produced procedural excellence while inadvertently discouraging mastery. An employee who can complete a form correctly is celebrated; an employee who questions whether the form captures what matters is often viewed as problematic.
This distinction is critical. Compliance ensures that work meets minimum standards; craftsmanship strives for excellence beyond what any checklist can capture. The former is necessary but not always sufficient. When organisations become overly reliant on compliance mechanisms, they risk creating what organisational psychologists term ‘procedural rigidity’, a condition where workers follow rules without understanding the underlying rationale, making them unable to adapt when circumstances change [10]. In science, this manifests as people who can execute protocols but cannot design robust experiments, or who can operate sophisticated equipment but cannot interpret anomalous results. Genuine expertise requires not just knowing that a procedure works, but understanding why it works, a distinction (that procedural systems often obscure) [11].
The pharmaceutical industry has become increasingly standardised, with formal processes governing every stage of drug development. While this has undoubtedly improved consistency and regulatory compliance, it has also created environments where critical thinking can become subordinate to box-ticking. The scientist who challenges a protocol design, questions a statistical approach, or suggests an alternative methodology may find themselves swimming against a powerful current of established procedure. The result is a workforce that is efficient but not necessarily insightful.
The introduction of tools like ChatGPT and other large language models into knowledge work represents both promise and peril. On the one hand, these technologies can streamline operations, aid discovery, and democratise access to expertise. On the other, they risk encouraging intellectual laziness and superficiality. Why wrestle with a complex concept when you can ask a chatbot? Although institutions involved in the pharmaceutical industry have introduced mechanisms to limit the risks associated with their use, many employees are still using them informally.
The critical question is not whether these tools are used, but how they are used. Here, a crucial distinction emerges: technology amplifies experts but substitutes for novices. As research on skill acquisition showed, novices rely on rules and procedures, while experts draw on tacit knowledge and intuition [12]. An experienced scientist can use AI to accelerate their thinking, generate hypotheses, and explore alternatives more rapidly. An inexperienced scientist, lacking the foundational knowledge to evaluate AI outputs critically, may use AI instead of thinking. The former represents augmentation; the latter represents deskilling.
Cognitive science identifies the 'Google Effect,' the tendency to outsource memory to technology, which weakens retention [13]. Similarly, over-reliance on AI risks what researchers call ‘automation bias’, the tendency to trust automated systems even when their outputs are flawed [14]. This dependency creates a competency gap, where workers lack the foundational knowledge to validate AI outputs, a vulnerability particularly concerning in high-stakes fields such as pharmaceutical development. If over-relied upon, such tools will erode the very muscle that drives scientific inquiry: cognitive curiosity sustained by effort.
A related phenomenon is ‘cognitive offloading’, the use of external tools to reduce internal cognitive demands [15]. While this can be beneficial for routine tasks, it becomes problematic when it replaces the deep engagement necessary for scientific insight. Wegner and Ward have documented how the mere expectation of future access to information can reduce our motivation to encode that information deeply [16]. As a scientist, I worry that the habit of deep engagement, reading beyond abstracts, challenging assumptions, designing rigorous experiments, is becoming endangered. The tools are not the enemy; the uncritical dependence on them is.
The verification burden created by AI tools is also worth noting. As these systems become more sophisticated, distinguishing between AI-generated and human-generated content becomes increasingly difficult. This places an additional burden on scientists to verify not only their own outputs but also those of their colleagues. The consequence may be a net increase in workload, particularly for those senior scientists charged with quality assurance [17].
It would be simplistic to attribute declining standards to individual failings. The systems within which scientists operate shape behaviour more powerfully than individual character. Key Performance Indicators, quarterly reporting requirements, publication metrics, venture capital expectations, and procurement processes collectively reward speed and volume over depth and rigour.
In academia, the pressure to publish (publish or perish) has incentivised quantity over quality, resulting in a proliferation of poorly controlled, statistically weak studies that cannot be replicated [18]. The replication crisis in psychology and biomedical research is not a failure of individual scientists but a systemic consequence of incentive structures that reward novel, positive findings over rigorous, null results [19]. Publication bias, the preferential publication of positive results, further distorts the scientific record, creating an evidence base that is systematically over-optimistic [20].
In industry, the valorisation of speed and innovation has created an unsustainable loop where appearances matter more than outcomes. The pharmaceutical industry's return on research and development investment has been declining for decades, prompting cost-cutting measures that may further compromise quality [21]. Short-term profit maximisation, driven by quarterly reporting cycles, incentivises incremental innovation over transformative discovery and expediency over thoroughness. These are not moral failings but rational responses to the incentives created by financial markets and organisational structures.
If standards are indeed slipping, the responsibility for addressing this does not lie solely with younger scientists. Experienced professionals have a duty to mentor, to model high standards, and to create environments where rigorous science can flourish. If younger scientists are reluctant to challenge assumptions, perhaps senior scientists have failed to create psychological safety where disagreement is welcomed rather than punished.
Research on psychological safety, the belief that one will not be punished for speaking up with ideas, questions, or concerns, demonstrates its critical importance for learning and innovation [22]. In psychologically safe environments, junior scientists feel empowered to question data inconsistencies, challenge flawed protocols, and propose alternative approaches. In environments where speaking up is seen as obstructionist, even the most conscientious young scientist will learn to remain silent.
The preservation of craftsmanship requires active mentorship. Experienced scientists must not only critique but also teach: explaining not just what to do but why it matters, demonstrating how to think critically about evidence, and modelling the intellectual honesty that underpins good science. Some have argued that expertise is not merely a matter of technical knowledge but involves tacit, embodied understanding that can only be transmitted through prolonged interaction [23]. This takes time and effort, we might traditionally have called it an apprenticeship, resources for this are increasingly scarce in productivity-focused organisations. Yet without such mentorship, the tacit knowledge that distinguishes master scientists from competent technicians will be lost.
The pharmaceutical industry exists at a uniquely tense intersection of innovation, human well-being, and commercial profit. It is a sector where success can genuinely change, or save, lives. But when the pursuit of shareholder returns dominates over scientific integrity, the consequences are dire. In the worst-case scenarios, we have seen manipulated clinical data, aggressive off-label marketing, and unethical pricing strategies [24][25]. Although a rather dated example, the opioid crisis in the United States stands as a testament to what happens when industry actors abdicate ethical responsibility in pursuit of revenue. Purdue Pharma's marketing of OxyContin as ‘non-addictive,’ despite clear evidence to the contrary, was not merely a lapse in judgment, but a systemic ethical failure [26]. Such events erode public trust and tarnish the legacy of legitimate scientific achievement.
The commercial pressures that drive such failures are not unique to the pharmaceutical industry, but they are particularly consequential given the life-or-death stakes involved. When financial incentives are misaligned with scientific rigour, the result is not just wasted resources but genuine harm to patients. Addressing this requires not only stronger regulation but also a cultural shift within organisations, one that values long-term integrity over short-term profit.
It is tempting to attribute these trends to a broader societal shift toward laziness or lack of commitment. Indeed, a perceived erosion of work ethic and diligence is a common refrain among senior professionals. But research suggests a more complex picture. Millennials and Gen Z workers are not necessarily less motivated, they are navigating a world of precarious employment, digital overload, and performance metrics driven by automation and algorithms [27]. Industry veterans can testify to increasing institutional commitment to rigour that has often taken the form of formal processes, guides, templates and 'tools.' The result, craftsmanship declines. In academia, the pressure to publish has incentivised quantity over quality, resulting in a proliferation of poorly controlled, statistically weak studies that cannot be replicated [18]. In industry, the celebration of speed and innovation has created an unsustainable loop where appearances matter more than outcomes.
The generational critique, while intuitively appealing, obscures more than it reveals. The challenges facing young scientists today are not primarily matters of character but of context. They work in environments where short-term metrics dominate, where job insecurity is pervasive, and where speaking up carries professional risk. To blame them for the consequences of these systems is both unfair and unhelpful.
So, back to the initial question: Am I just repeating a generational cycle of grumbling? Or are my observations grounded in reality? Having acknowledged the substantial psychological literature on declinism, I turn to whether this time might genuinely be different.
Contemporary shifts differ in scale and irreversibility from what we have seen before. Unlike the slow adoption of calculators, AI's integration into professional life is unprecedented in its speed and breadth. The automation of cognitive tasks that were once the exclusive domain of human experts represents a qualitatively different phenomenon from previous technological disruptions [28]. Similarly, globalisation and algorithmic profit-maximisation have entrenched ethical shortcuts in ways that 20th-century business leaders could scarcely imagine.
Perhaps the answer is both. Ageing sharpens awareness of systemic patterns while simultaneously steeping us in personal biases. But experience does offer a broader temporal lens, one that differentiates trends from anecdotes. From that vantage point, I contend that much of what I see is not simply change, but degradation, particularly of scientific diligence, ethical accountability, and a sense of professionalism. The cognitive biases described above suggest that this perception may be partly distorted, but the systemic changes documented in the scientific literature provide reason for genuine concern.
That degradation is not irreversible. But it will not be corrected by nostalgia. It requires leaders, especially experienced ones, to model high standards, mentor with conviction, emphasise craftsmanship, and speak out when systems reward mediocrity over mastery. In the current environment, however, leadership is somewhat corporate in nature. A business's enthusiasm for AI often stems from cost-cutting targets rather than quality enhancement. The rush to automate professional work reflects a broader trend toward treating knowledge work as interchangeable and readily substitutable, a trend that fundamentally misunderstands the nature of expertise.
Those who know me will also know that I often reflect on whether my growing disillusionment with the state of our professional world is the inevitable grumbling of an ageing curmudgeon, or a warranted observation from a seasoned veteran witnessing the erosion of values that once underpinned our highest aspirations. This question is not merely rhetorical; it touches the core of how society and science progress.
A good scientist questions everything, particularly their own conclusions. The psychological literature on declinism, rosy retrospection, and related biases compels us to examine our perceptions critically. Yet to observe a general cultural slide toward the expedient, the superficial, and self-serving box-ticking, especially in fields as vital as ours, is not simply a matter of personal irritation. It is a call to action.
The challenge lies not in rejecting change, but in steering it with wisdom. Technology should augment expertise, not substitute for it. Systems should reward rigour, not speed. And the experienced among us should mentor rather than merely criticise. At Niche, we make an effort to combine the contributions of both the old and the new to the benefit of our team, and what a great team they are. I am happy to share our many recommendations, many of which are available on our website: www.niche.org.uk.
History shows that progress need not sacrifice rigour or morality. The world will always change, but values, truth, rigour, responsibility, should not be so easily negotiable. If that belief makes me a curmudgeon, I will wear the title with pride.
References
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