Many believe that the single most significant development over the past 500 years, in terms of cultural influence, technological innovation, and social transformation, has been the emergence of modern science. Science has come to represent the dawning of a new era, the ascent of humanity out of an age of blind dogmatism and into the clear daylight of procedural rationality and empiricism.

Yet contrary to popular belief, the ascent of humanity to procedural rationality and empiricism was first described in the story of Genesis. This is captured when, in front of the Tree of Knowledge, Adam and Chava (Eve) are enticed by the serpent to eat the forbidden fruit. Shaped by the Christian doctrine, eating the forbidden fruit from the tree of knowledge was a rebellion against God, the punishment for which was the infectious stain of evil on all descendants of Adam and Eve. Consequently, humans have been lost in a state of sin.

But this is not the only understanding of that story. And, importantly, this is not the only conceptual explanation of the relationship between knowledge and sin. 

Talmudic sages viewed knowledge and sin as intimately connected. Before eating the forbidden fruit, they believed that humanity originally acted according to truth (emet; אֶמֶת) and falsehood sheker; שֶׁקֶר), sharing God’s perfect, a priori knowledge. After eating fruit from the Tree of Knowledge, humanity now possesses empirical knowledge (a posteriori) with subjective, moral categories of good and evil. These subjective moral categories formed into two inclinations: yetzer hatov (יִצְרָה טוֹבָה; the good inclination) and yetzer hara (יַצֶר הָרָע; the evil inclination) (Talmud, Berakhot 61a). 

What can we make of this interpretation of the connection between sin and the Tree of Knowledge? Often interpreted as the original sin of humanity, or a moral of human limitation or even sexual desire, the passage, whose internal logic gestures toward a different reading, can instead be taken to suggest that at the root of empirical knowledge there exists an inextricable pairing of creativity and harm.  

I argue that epistemic harm is constitutive of empirical knowledge and that once this is recognized, it becomes clear that we bear moral responsibility toward epistemic disadvantage. I demonstrate that epistemic harms are treated in much social epistemology literature as counter to flourishing and something to be avoided. Against this framing, I argue that the yetzer hara (evil inclination) simultaneously animates discovery and generates exclusion. These are not separable. But to be precise about our responsibility, we need a taxonomy that shows the variety of epistemic harms in epistemic practice.

Exploitation, a recurring concern in both ethics and political philosophy, has recently garnered increasing attention amongst philosophers of science and epistemologists. Exploitative knowledge-practices are being explored under the guise of epistemic exploitation, and a number of accounts detailing the harms and wrongs of such exploitation have been developed. However, these accounts diverge in normatively significant ways on both the central wrong of, and the harms associated with, epistemic exploitation. Further, I will argue, extant accounts of epistemic exploitation remain too narrow to appropriate capture the many different ways in which epistemic practices can become exploitative. My primary aim in this paper is to develop a conception of epistemic exploitation that can capture this diversity, while at the same time account for the harms and wrongs of epistemic exploitation that have been identified in the literature. At the same time, in doing so I aim to re-conceptualisation the central wrong of epistemic exploitation, to insulate it from challenges based in the nonworseness claim.

In order to do so, I examine the extant literature on epistemic exploitation and of exploitative research practices to elucidate the diversity in how these accounts conceive of what makes epistemic exploitation wrong, and the primary harms that such practices produce. Following that I draw on longstanding debates in applied ethics to introduce the nonworseness claim as a challenge to existing accounts of epistemic exploitation. In light of this challenge, I argue that any satisfactory conception of epistemic exploitation ought to be able to account for both mutually beneficial and structural forms of exploitation. In addition, I argue that such an account ought to be able to handle the normative questions that arise out of the complex choice situations facing the exploited. Especially given the prevalence, and (possibly?) unavoidability of harm in our epistemic lives. Having identified these desiderata, I begin developing such an account centred around an account of exploitation that centres inferiority, drawing on recent work in political philosophy. I conclude the paper by briefly discussing the implications of this account of epistemic exploitation for some of the solutions and mitigating strategies that have been proposed to address exploitative epistemic practices in science and education, including extractivist research practices.

Loneliness rating scales are one of the primary technologies used to create data on loneliness, with extensive application and adaptation in contemporary research. While they have been subject to considerable criticism, this has so far stayed within specific procedural bounds, and can best be understood as part of a process of methodological refinement. Left untroubled are two interrelated – and shaky – assertions: that there is something to measure, the measurand, and that the properties of the measurand are measurable by any means; and that the tools in front of us are – or can be improved to be – tools capable of measuring that measurand. By staying on this terrain, debates over loneliness measurement feed a mythos which accrues epistemic authority and blackboxes a series of vexed and important epistemic processes; they pull attention to their inputs and outputs, but not where they come from or what they actually do. This paper surfaces two areas of tension: the historical creation of the UCLA loneliness scale, which symbolised and enacted a seismic theoretical and practical shift in how knowledge and evidence on loneliness has been constituted and obtained; and what the theorist of measurement Jana Uher calls the ‘intricate demands’ that measurement makes on the rater, the person invited to quantify their experience. It then situates these questions in dialogue with work on epistemic extractivism, research ethics, harmful inclusion, and the social and political life of quantitative data. 

It is well-established that algorithms can be instruments of injustice. It is less frequently discussed, however, how current modes of AI deployment often make the very discovery of injustice difficult, if not impossible. In this article, we focus on the effects of algorithmic profiling on epistemic agency. We show how algorithmic profiling can give rise to epistemic injustice through the depletion of epistemic resources that are needed to interpret and evaluate certain experiences. By doing so, we not only demonstrate how the philosophical conceptual framework of epistemic injustice can help pinpoint potential, systematic harms from algorithmic profiling, but we also identify a novel source of hermeneutical injustice that to date has received little attention in the relevant literature, what we call epistemic fragmentation. As we detail in this paper, epistemic fragmentation is a structural characteristic of algorithmically-mediated environments that isolate individuals, making it more difficult to develop, uptake and apply new epistemic resources, thus making it more difficult to identify and conceptualise emerging harms in these environments. We thus trace the occurrence of hermeneutical injustice back to the fragmentation of the epistemic experiences of individuals, who are left more vulnerable by the inability to share, compare and learn from shared experiences.

This contribution presents empirical and normative findings on harms and epistemic injustices in the context of a large international biomarker consortium. In the first study, a qualitative interview study, we identified multifaceted forms of harm and ethical issues related to medical data-intensive biomarker development and application. Based on this, in a second study, we conducted philosophical-theoretical analyses regarding the extent to which the concept of harm applied matters for ethical deliberations and harm-benefit analyses. By applying three philosophical frameworks – the temporal, counterfactual and non-comparative account to harm – we showed that different concepts of harm can lead to substantially different assessments and recommendations for action. The results demonstrate that explicit consideration of different concepts of harm is essential for nuanced ethical deliberation in healthcare, and for avoiding overlooked perspectives and miscommunication. Furthermore, the interviewees from the first study implicitly described epistemic injustices in biomarker development when referring to harm. In a third study, I describe and analyse three scenarios: 1. biomarkers indicating disease severity, 2. absent biomarkers for particular subgroups, and 3. emerging data-driven disease classification systems. These scenarios illustrate how various forms of epistemic injustice with their distinct structural and systemic dimension may emerge from opacities of machine learning, data dependency, and conceptual assumptions regarding disease. I further examine the risks associated with overattributing epistemic authority to artificial intelligence and large-scale data in biomarker contexts, alongside the risk of systemic and structural manifestations of epistemic injustices in institutions as data-intensive biomarkers and disease classification systems gain wider adoption. I close with reflections on the relationship of epistemic injustice and harm in the contexts described and suggestions on how to promote epistemic justices and mitigate harms. Recognising and addressing these frequently difficult-to-detect epistemic injustices and multifaceted harms while promoting epistemic justice is essential for just and transparent use of big data and artificial intelligence for biomarkers in healthcare. Note: The content of this abstract is drawn from two article-based doctoral dissertations by Marie-Christine Fritzsche and the corresponding manuscripts.

The idea that some ecosystems are in good or bad condition hardly seems controversial. And yet, dig deeper into discussions of ecosystem health, and a broad scepticism emerges: few people seem to think that ecosystems can literally be healthy; often because they do not have the right features to ground a clear set of interests. Here, I argue that questions about ecosystem health are best considered as methodological ones, i.e., ‘what methods are required to evaluate the condition of an ecosystem?’. I offer a solution which combines the study of value relations between humans, non-humans, and their environments, alongside measurement of the preconditions for these. The result is an account of ecosystem health which is neither unequivocal nor arbitrary, but instead is indexed to the organisms and processes we care about.

During fieldwork at the Crops Research Institute, a disagreement over cassava planting practices revealed deeper tensions about what counts as reliable knowledge. Technicians advocated the two-node cutting method as scientifically efficient, while farmers insisted on four, a practice rooted in soil conditions, rainfall uncertainty, and accumulated cultivation experience. This divergence was not resistance but an epistemically grounded response to environmental unpredictability. Using this case, the paper applies the concept of hermeneutical inequality to agricultural research, showing how institutional protocols may obscure local knowledges. One observation we will make is that hermeneutical gaps can generate both epistemic injustice and epistemic disadvantage, the latter not typically linked to such gaps. By teasing apart these outcomes, we highlight communicative dynamics where knowledge from farmers is used but participants are treated as sources rather than informants—what Fricker terms epistemic objectification. This analysis invites reflection on co-production, legibility, and epistemic loss in agricultural science.

This paper examines climatic practices in the northern Naqab^[1] through the case of the Yatir Forest, where KKL-JNF’s^[2] project of “turning the desert green” functions as a desert laboratory for ecological domination under settler colonial rule. Rather than treating afforestation as a neutral environmental intervention, the paper frames it as a site where techno-scientific authority—produced through collaborations between KKL-JNF and Ben-Gurion University scientists—generates epistemic harm. Scientific expertise becomes a mechanism for legitimizing land dispossession, erasing Bedouin ecological knowledge, and naturalizing settler claims to the landscape.

By bringing together scholarship on environmental violence, epistemological violence, and decolonization, the paper develops an approach that highlights “climatic Indigenous Bedouin knowledge” as a counter-epistemology that unsettles these scientific narratives. Despite the centrality of tree-planting to Israeli environmental governance, the techno-scientific authority behind afforestation remains largely unexamined. The Yatir case reveals how ecological research, measurement practices, and climate discourse become entangled with colonization, producing hierarchies of credibility that render Bedouin experiences and land relations illegible.

The paper shows how epistemic harm operates through both knowledge production and knowledge exclusion. It offers a framework for understanding how environmental governance in Palestine manufactures ignorance, and how Indigenous counter-knowledge articulates forms of ecological resistance.

^[1] The Naqab (Negev) is the southern half of historic Palestine, home to roughly 300,000 Palestinian Bedouins. Since 1948, the region has been a central site of dispossession, forced sedentarization, and environmental restructuring under Israeli state planning.

^[2] KKL-JNF (Keren Kayemeth LeIsrael–Jewish National Fund) is a quasi-governmental land and development agency established in the early 20th century to acquire and manage land for Jewish settlement. Today it operates as a major actor in afforestation, land planning, and ecological projects, often advancing state territorial policies through environmental and scientific interventions.

What did therapeutic case-writing do for medico-psychological knowledge-making? While significant scholarship has examined what it means to ‘think in cases’ for the purposes of psychiatric diagnosis or accounting for extraordinary subjects, we know much less about the epistemic dynamics of case histories focused on therapy. Yet practitioners of widespread talk psychotherapies have frequently textualized and published accounts of their cases, from the beginnings of ‘psychotherapy’ as a named practice in the 1890s with Hippolyte Bernheim’s use of (hypnotic) suggestion. If Bernheim was known (and later critiqued) for the rather authoritarian way he directed verbal suggestions to patients—‘your fits will disappear’—his own doubts and conceptual reasoning are also narrativized in some of his psychotherapeutic observations, allowing readers to re-produce the process of therapeutic sense-making for themselves. Bernheim’s readers, then, would seem to be included more actively in the knowledge-making process than are his patients in the therapeutic process. In this paper, I explore the dynamics of epistemic inclusion and exclusion that play out between therapist and patient, and narrator and reader, as part of a larger project interrogating the intersection of textual practices, therapeutic practices, and epistemic functions in psychotherapy case-writing. Do therapist-narrators tend to provide direction to their patients and readers in similarly open or closed forms? What might it mean for the epistemic stakes of case-writing for there to be an asymmetry between a therapist-narrator’s treatment of patients and readers, as in Bernheim’s case?

Within patient communities, members often share valuable resources to aid patients in navigating complex and opaque healthcare institutions. This often serves as a means to promote the epistemic agency of patients who would otherwise struggle to engage successfully to achieve the outcomes needed. In this paper, I explore the harms to epistemic agency which arise from opaque healthcare institutions even when patients find successful routes for navigating them and exercising their epistemic agency. 

Healthcare institutions are often ‘opaque’: ‘increasingly resistant to assessment and understanding by their agents and, especially, their users’ (Carel and Kidd, 2021, p.481). They often have complex and unknown bureaucratic processes, hidden norms and limited challenges for communication, access and engagement. Without a high level of idiosyncratic knowledge and skill in navigating them, it can be difficult to gain access to appointments and appropriate referrals, let alone diagnosis, treatment and support. 

Carel and Kidd observe that opaque institutions ‘frustrate individual-level epistemic agency’ (ibid., p. 482) because individuals are prevented from effective engagement with the institution. However, some patients, especially those who pool knowledge and seek advice from others in similar positions, become skilled at navigating healthcare institutions. They learn who they need to speak to in order to get the referrals they need, how to interact with doctors so that they will be taken seriously, which specialists to request, and so on. This allows them to regain some epistemic agency.

In this paper, I focus specifically on the harm done to those patients who develop the skills and knowledge to navigate opaque healthcare institutions. It is possible that these patients develop what I call ‘resistant epistemic agency’ because they increase their repertoire of skills and techniques for successfully engaging with healthcare institutions. They may develop alternative and ‘sub-terranean’ routes for achieving desired outcomes. However, greater skill in navigating opaque institutions does not necessarily equal a stronger form of epistemic agency. I argue that this form of resistant epistemic agency’displayed by skilled patients can be both insecure and costly. 

References

Havi, Carel & Kidd, Ian James (2021). Institutional Opacity, Epistemic Vulnerability, and Institutional Testimonial Justice. International Journal of Philosophical Studies. 29 (4):473-496.

The emerging field of digital phenotyping promises to revolutionize psychiatry by identifying behavioral patterns relevant to the emergence of mental health symptoms, such as delusions or low mood. Through digital devices, such as smartphones and wearables, large amounts of data are continuously collected, including mobility patterns, social media interactions, typing speed and voice fluctuations. From these patterns, indicators and predictors of changes in the user’s mental well-being are identified. According to many of the proponents of the approach (e.g., Insel 2018), this could grant the patients privileged access into their mental life in a way that is subjectively difficult to grasp. Next to this, the risk factors identified through digital phenotyping would grant the users the possibility for better self-management, by accurately responding to the indicators and early warning signs. Accordingly, the framework is often presented as “participatory” (e.g., Zhang et al. 2025) or even “empowering” (e.g., Hsin et al. 2018). 

In this paper, I argue that digital phenotyping risks causing epistemic harm to the users of the tool by capturing superficial behavioral patterns, detached from their personal significance. This can significantly undermine the capacity for self-understanding, which is often crucial for recovery from mental distress. First, digital phenotyping may identify markers that are experientially meaningless to the patient. When an app alerts someone to risk factors that they cannot meaningfully integrate into their self-concept, this could lead to self-alienation. The user may begin to distrust their own experience, or even develop distress in response to the system’s warnings – creating a self-fulfilling prophecy.

Second, in many cases of mental health issues, short-term improvements in mood arise from coping mechanisms that are ultimately destructive, such as constant social engagement to avoid loneliness, excessive exercise to maintain control, or overwork to suppress anxiety. By identifying correlations between such behaviors and transient mood improvements, digital phenotyping may hinder the capacity to understand these deeper lying issues, and thereby the capacity for genuine improvement. It may even recommend their continuation, which would reinforce the very dynamics that sustain the problem. In both of these cases, digital phenotyping is rather disempowering, by undermining the capacity for genuine self-understanding. 

Participatory research (PR) is widely promoted as a corrective to epistemic injustice, seeking to redress the historical exclusion of marginalized communities from the production of scientific knowledge. Yet, despite its emancipatory intent, PR often reproduces or exacerbates epistemic harms, e.g. through epistemic exploitation (Berenstain 2016), contributory injustice (Dotson 2012), and the epistemic appropriation of lived experience (Davis 2018; Podosky 2023; Pohlhaus 2020; Medina 2022). This paper asks what it would mean for participatory research to actually realize epistemic justice.

To this end, I position ‘restorative epistemic justice’ as a framework for assessing PR. Drawing on a relational and non-ideal understanding of epistemic repair (Almassi 2018; Walker 2006), I propose that participatory practices are epistemically just to the extent that they contribute to the restoration of epistemic relationships between research and participant communities. For PR to be epistemically just in this robust sense entails two conditions. First, reparative efforts must extend beyond discrete acts of participation and individual agents of injustice, aiming instead to restore relations between epistemic communities. Second, for participation to restore such communal relationships, epistemic repair should be aimed at the norms and infrastructures that sustain unjust practices, rather than (merely or primarily) the epistemic character of researchers.

Through field observations of R2D2-MH, a participatory biomarker development project in autism research, I note how data infrastructures can become sites of epistemic repair. One of R2D2-MH’s central outcomes is the co-design of an explicitly neurodiversity-affirmative ICF Core Set for data harmonization, positioned as an “authoritative” epistemic resource to “facilitate neurodiversity-affirmative investigation” (Black et al. 2025, 115). This effort, to the extent it finds communal uptake, exemplifies (an attempt at) restorative epistemic justice: it proceeds from the interests and values of a historically marginalized community and renegotiates exclusionary epistemic norms through the material reform of research infrastructure.

In sum, by positioning restorative epistemic justice as an evaluative framework for participatory research, this paper offers a lens for understanding when and how PR may realize its (epistemically) emancipatory aims. Rather than treating participation as inherently (un)just, this framework directs attention to whether participatory practices restore epistemic relationships between research and marginalized communities. The case of data infrastructure reform illustrates one way through which participatory practices can enact epistemic repair at such a more systemic level.

The human face has more recently become a source of medically relevant information and a symbol of medical innovation—from automatically revealing subtle indicators of genetic conditions to signaling expressions of pain or well-being. With the rapid advancement of AI and proliferation of facial recognition technologies, the algorithmic diagnosis of faces in clinical and healthcare environments is expanding. This paper examines the data journeys of medical faces: their capture, production, circulation and automated evaluation, as well as the personal, social and epistemic economies that shape and are shaped by these data movements. The paper first situates the analysis in the context of facial recognition in rare disease detection, where facial traits are coded and algorithmically processed, and circulated as what could be termed “code/face” to support diagnostic decision-making. It then discusses the personal and social economy around the face as traveling data—tracing how hopes, uncertainties, and promises are built into the vehicles and infrastructures of data journeys, and how personal value is here weighted and exchanged against social risks and potential harms. In a next step, the broader epistemic economy of data journeys will be addressed, which rests on the twin ideals of frictionless data sharing and techno-solutionism, yet at the same time being entangled in complex relationships with political-regulatory spaces. Finally, the paper reflects on how these intersecting economies can inform both our conceptual and methodological understanding of data mobilities.

Many who engage in the concept of epistemic injustice simply state that this phenomenon occurs when ‘someone is wronged in their capacity as a ‘knower’. But what does it really mean to be wronged as a knower? While Fricker offers interesting discussions of being degraded ‘as a human being’, and profound disruptions of one’s identity (on a personal and structural level), the existential impact of this harm has been underexplored. To expand on Fricker’s theory, this talk addresses the wide-reaching reverberations epistemic harm elicits across the self, being-in-the-world, intentionality, and intersubjectivity. Through a phenomenological approach, this talk will draw out the multi-level existential harms that epistemic injustice produces, from the primordial level of a breakdown in Self-Other recognition, to the ‘inhibited intentionality’ of being unable to act in the world as an epistemic agent. This phenomenological account aims to both illuminate the full extent of the damage epistemic injustice can inflict on a marginalised individual, and to disentangle epistemic harm as a distinct and insidious kind of harm. 

This paper extends the concept of epistemic harm into the domain of fair and ethical artificial intelligence, with a focus on machine learning-based medical decision-making. While fairness in machine learning has been theorized in relation to justice, the literature often overlooks how predictive models generate harms—particularly epistemic harms—across different actors. We argue that epistemic harms arise not only for patients subject to opaque, black-box decisions, but also for data scientists building models, and practitioners such as judges or doctors relying on them. Ex post explanations of model predictions, while intended to improve transparency, introduce a novel epistemic harm when explanations are inaccurate. Situating these concerns within probabilistic (non-deterministic) domains such as medical prediction, we highlight the limits of eliminating harm entirely, while questioning whether harms should always be avoided.

The emergence of AI has allowed a new type of epistocratic governance to emerge: AI-ocracy. The democracy/epistocracy debate considers the plausibility of weighted votes in elections. In contrast, AI-ocracy empowers AI to weigh voices during online deliberations. This paper uses a Condorcetian model of democracy to show how the expected benefits of epistocratic governance translate into actual epistemic harms. In particular, AI domination—as a technology-driven type of domination—allows an alien type of algorithmic rationality to compromise truth-oriented politics with an engagement-oriented deliberative environment that manipulates particular people and the general deliberative process itself. Most significantly, AI amplifies engaging but simplistic narratives that intentionally maximise engagement but unintentionally maximise emotions, which unintentionally minimises the independence, competence and sincerity of voters. So, AI domination threatens to invert the tendency of deliberation to cultivate our Condorcetian characteristics and compromises the competence of democracy itself. 

Harm is manifest in the Ecuadorian Amazon. It is evident, persistent, and unrelenting for those living alongside the oil industry. At the same time, harm is often slippery, its presence difficult to confirm or discern. How do we know harm when we encounter it? Over the course of two years of ethnographic fieldwork, I explored how scientific, regulatory, legal and social practices are all significant interventions into the consequences of oil extraction: such interventions lend harm weight, make it visible, legible, or countable in different forums. My intention in exploring these practices was not to bound or define harm as one thing or another but rather to show how the relationality of harm from oil extraction actually emerges through these interventions. Harm, in this sense, is both a relationship and an animating feature of relationships in spaces of extraction. In this talk, I explore how an ethnographic attention to harm in the context of one extractive industry (oil) might be productively extended to (and challenged) in the context of another set of extractive industries, namely artificial intelligence (AI). If a relational approach to harm requires reckoning with the legacies upon which extractive systems are built, how can broad forms of accountability that extend beyond legal and regulatory understandings be cultivated in the age of AI?  What would reparations look like in response to epistemic harms resulting from AI? Attention to the relationality of harm can illustrate why other ways of understanding harm matter, and why we harm as relation might help to contemplate what comes next when living in a world shaped by multiple extractivisms.

Solidarity is a critical yet underexplored dimension of social cohesion and, in fact, democracy. Despite its importance, we know little about the epistemic conditions that facilitate the emergence and sustainability of solidarity. This paper investigates the forms of epistemic states—encompassing knowledge, attitudes, skills, and practices—that may underpin and enable solidarity. Specifically, we explore how trust, experiential knowledge, and social identity contribute to the creation and maintenance of solidarity, while also addressing the risks of misappropriated or problematic forms of solidarity.
We propose that knowledge conducive to solidarity involves both trust in the existence of relevant institutions and the ability to identify and interact productively with them. This trust is often grounded in experiential knowledge, where past interactions reassure individuals and groups of the reliability and potential of specific actors—whether individuals, groups, or institutions—to provide support. While solidarity cannot be reduced to mere reciprocity, the reliability of expectations and the ability to elicit appropriate responses are central to its durability.
Social experience and identity also play a crucial role in fostering solidarity. Self-identification and how people perceive themselves within a collective context shape their capacity to engage in and sustain solidarity. Furthermore, the intersection of solidarity with intimacy and meaningful information exchange raises important questions about the cognitive and relational underpinnings of solidarity. Drawing on Bergson’s idea of love and Leonelli’s concept of “judicious connections,” we explore how caring relations and humane openness facilitate meaning-making and actionable knowledge, which are essential for solidarity.
Finally – and linking explicitly to the collection focus on epistemic harms – we address the risks of problematic forms of solidarity or lack thereof, including situations where erraticism, deceit, misguided expectations or intolerance make solidarity untrustworthy or outright harmful. Judicious connections, we argue, play an important role in avoiding such problematic forms of solidarity, even as they themselves involve discrimination in committing to specific relations over others. States of solidarity involve consistently focusing attention on a select few interlocutors, to the exclusion of many others – generating harm in the shape of a loss of diversity among relevant actors. Listening as a political activity (e.g., Dobson) emerges as a critical practice to mitigate this harm and retain enough openness to effectively adapt to an ever-changing world.