To assess or not to assess: Ethical issues in online assessments

Salimuddin, S., Beshai, S., & Loutzenhiser, L. (2025).

Canadian Psychology / Psychologie canadienne.

Advance online publication.

https://doi.org/10.1037/cap0000423

Abstract

There has been a proliferation of psychological services offered via the internet in the past 5 years, with the COVID-19 pandemic playing a large role in the shift from in-person to online services. While researchers have identified ethical issues related to online psychotherapy, little attention has been paid to the ethical issues surrounding online psychological assessments. In this article, we discuss challenges and ethical considerations unique to online psychological assessments and underscore the need for targeted discussions related to this service. We address key ethical issues including informed consent, privacy and confidentiality, competency, and maximizing benefit and minimizing harm, followed by a discussion of ethical issues specific to behavioural observations and standardized testing in online assessments. Additionally, we propose several recommendations, such as integrating dedicated training for online assessments into graduate programmes and expanding the research on cross-modality reliability and validity. These recommendations are closely aligned with principles, standards, and guidelines from the Canadian Code of Ethics for Psychologists, the Canadian Psychological Association Guidelines on Telepsychology, and the Interim Ethical Guidelines for Psychologists Providing Psychological Services via Electronic Media.

Impact Statement

This article provides Canadian psychologists with guidance on the ethical issues to consider when contemplating the remote online administration of psychological assessments. Relevant sources, such as the Canadian Code of Ethics for Psychologists, are used in discussing ethical issues arising in online assessments. 

Here are some thoughts:

The core message is that while online assessments offer significant benefits, especially in terms of accessibility for rural, remote, or underserved populations, they come with a complex array of unique ethical challenges that cannot be ignored. Simply because a service can be delivered online does not mean it should be, without a thorough evaluation of the risks and benefits.

Embrace the potential of online assessments to increase access, but do so responsibly. Prioritize ethical rigor, client well-being, and scientific validity over convenience. The decision to assess online should never be taken lightly and must be grounded in competence, transparency, and a careful weighing of potential harms and benefits.

The new self-care: It’s not all about you.

Barnett, J. E., & Homany, G. (2022).

Practice Innovations, 7(4), 313–326.

https://doi.org/10.1037/pri0000190

Abstract

Clinical work as a mental health practitioner can be very rewarding and gratifying. It also may be stressful, difficult, and emotionally demanding for the clinician. Failure to sufficiently attend to one’s own functioning through appropriate ongoing self-care activities can have significant consequences for the practitioner’s personal and professional functioning to include experiencing symptoms of burnout and compassion fatigue that may result in problems with professional competence. The American Psychological Association (2017) ethics code mandates ongoing self-monitoring and self-assessment to determine when one’s competence is at risk or already degraded and the need to then take needed corrective actions. Yet research findings demonstrate how flawed self-assessment is and that many clinicians will not know when assistance is needed or what support or interventions are needed. Instead, a communitarian approach to self-care is recommended. This involves creating and actively utilizing a competence constellation of engaged colleagues who assess and support each other on an ongoing basis. Recommendations are made for creating a self-care plan that integrates both one’s independent self-care activities and a communitarian approach. The role of this approach for promoting ongoing wellness and maintaining one’s clinical competence while preventing burnout and problems with professional competence is accentuated. The use of this approach as a preventive activity as well as one for overcoming clinician biases and self-assessment flaws is explained with recommendations provided for practical steps each mental health practitioner can take now and moving forward.

Impact Statement

This article addresses the important connections between clinical competence, threats to it, and the role of self-care for promoting ongoing clinical competence. The fallacy of accurate self-assessment of one’s competence and self-care needs is addressed, and support is provided for a communitarian approach to self-care and the maintenance of competence.

A pdf is here.

Shaping the Future of Healthcare: Ethical Clinical Challenges and Pathways to Trustworthy AI

Goktas, P., & Grzybowski, A. (2025).

Journal of clinical medicine, 14(5), 1605.

https://doi.org/10.3390/jcm14051605

Abstract

Background/Objectives: Artificial intelligence (AI) is transforming healthcare, enabling advances in diagnostics, treatment optimization, and patient care. Yet, its integration raises ethical, regulatory, and societal challenges. Key concerns include data privacy risks, algorithmic bias, and regulatory gaps that struggle to keep pace with AI advancements. This study aims to synthesize a multidisciplinary framework for trustworthy AI in healthcare, focusing on transparency, accountability, fairness, sustainability, and global collaboration. It moves beyond high-level ethical discussions to provide actionable strategies for implementing trustworthy AI in clinical contexts. 

Methods: A structured literature review was conducted using PubMed, Scopus, and Web of Science. Studies were selected based on relevance to AI ethics, governance, and policy in healthcare, prioritizing peer-reviewed articles, policy analyses, case studies, and ethical guidelines from authoritative sources published within the last decade. The conceptual approach integrates perspectives from clinicians, ethicists, policymakers, and technologists, offering a holistic "ecosystem" view of AI. No clinical trials or patient-level interventions were conducted. 

Results: The analysis identifies key gaps in current AI governance and introduces the Regulatory Genome-an adaptive AI oversight framework aligned with global policy trends and Sustainable Development Goals. It introduces quantifiable trustworthiness metrics, a comparative analysis of AI categories for clinical applications, and bias mitigation strategies. Additionally, it presents interdisciplinary policy recommendations for aligning AI deployment with ethical, regulatory, and environmental sustainability goals. This study emphasizes measurable standards, multi-stakeholder engagement strategies, and global partnerships to ensure that future AI innovations meet ethical and practical healthcare needs. 

Conclusions: Trustworthy AI in healthcare requires more than technical advancements-it demands robust ethical safeguards, proactive regulation, and continuous collaboration. By adopting the recommended roadmap, stakeholders can foster responsible innovation, improve patient outcomes, and maintain public trust in AI-driven healthcare.

A pdf is here.

Here are some thoughts:

This article is important to psychologists as it addresses the growing role of artificial intelligence (AI) in healthcare and emphasizes the ethical, legal, and societal implications that psychologists must consider in their practice. It highlights the need for transparency, accountability, and fairness in AI-based health technologies, which can significantly influence patient behavior, decision-making, and perceptions of care. The article also touches on issues such as patient trust, data privacy, and the potential for AI to reinforce biases, all of which are critical psychological factors that impact treatment outcomes and patient well-being. Additionally, it underscores the importance of integrating human-centered design and ethics into AI development, offering psychologists insights into how they can contribute to shaping AI tools that align with human values, promote equitable healthcare, and support mental health in an increasingly digital world.

When are health professionals ethically obligated to engage in public advocacy?

Wynia, M. K., Peek, M. E., & Heisler, M. (2025).

The Lancet.

https://doi.org/10.1016/s0140-6736(25)01378-9

Here is how it opens:

In 2025 the US Federal Government has attacked scientific research and evidence, medical expertise, public health, health equity, and human rights. At this challenging time, many health professionals are uncertain about what is in their power to change, and whether or how they may be ethically obligated to engage in public advocacy.

While clinical advocacy on behalf of individual patients is a long-standing core value across health professions, clinicians also have public advocacy obligations. For health professionals, one definition of public advocacy is taking actions to promote “social, economic, educational, and political changes that ameliorate suffering and contribute to human well-being” that are identified through “professional work and expertise”. Public advocacy obligations are in the Physician Charter, endorsed by 109 organisations internationally, and the American Medical Association’s Declaration of Professional Responsibility, endorsed by almost 100 US medical associations. Nearly two-thirds of US medical schools’ curricula include teaching on public advocacy skills.

Here are some thoughts:

Psychologists have an ethical duty to advocate against policies harming mental health and human rights, grounded in principles of justice and beneficence. When witnessing harm directly, possessing relevant expertise, or being positioned to create change—such as documenting trauma in marginalized groups or analyzing mental health impacts of funding cuts—advocacy becomes imperative. While fears of backlash exist, collective action through professional organizations can reduce risks. Psychologists must leverage their unique skills in behavioral science and public trust to combat misinformation and promote evidence-based policies. Advocacy isn't optional—it's core to psychology's mission of reducing suffering and upholding equity, especially amid growing threats to vulnerable populations. 

Large language models show amplified cognitive biases in moral decision-making

Cheung, V., Maier, M., & Lieder, F. (2025).

PNAS, 122(25).

https://doi.org/10.1073/pnas.2412015122

Abstract

As large language models (LLMs) become more widely used, people increasingly rely on them to make or advise on moral decisions. Some researchers even propose using LLMs as participants in psychology experiments. It is, therefore, important to understand how well LLMs make moral decisions and how they compare to humans. We investigated these questions by asking a range of LLMs to emulate or advise on people’s decisions in realistic moral dilemmas. In Study 1, we compared LLM responses to those of a representative U.S. sample (N = 285) for 22 dilemmas, including both collective action problems that pitted self-interest against the greater good, and moral dilemmas that pitted utilitarian cost–benefit reasoning against deontological rules. In collective action problems, LLMs were more altruistic than participants. In moral dilemmas, LLMs exhibited stronger omission bias than participants: They usually endorsed inaction over action. In Study 2 (N = 474, preregistered), we replicated this omission bias and documented an additional bias: Unlike humans, most LLMs were biased toward answering “no” in moral dilemmas, thus flipping their decision/advice depending on how the question is worded. In Study 3 (N = 491, preregistered), we replicated these biases in LLMs using everyday moral dilemmas adapted from forum posts on Reddit. In Study 4, we investigated the sources of these biases by comparing models with and without fine-tuning, showing that they likely arise from fine-tuning models for chatbot applications. Our findings suggest that uncritical reliance on LLMs’ moral decisions and advice could amplify human biases and introduce potentially problematic biases.

Significance

How will people’s increasing reliance on large language models (LLMs) influence their opinions about important moral and societal decisions? Our experiments demonstrate that the decisions and advice of LLMs are systematically biased against doing anything, and this bias is stronger than in humans. Moreover, we identified a bias in LLMs’ responses that has not been found in people. LLMs tend to answer “no,” thus flipping their decision/advice depending on how the question is worded. We present some evidence that suggests both biases are induced when fine-tuning LLMs for chatbot applications. These findings suggest that the uncritical reliance on LLMs could amplify and proliferate problematic biases in societal decision-making.

Here are some thoughts:

The study investigates how Large Language Models (LLMs) and humans differ in their moral decision-making, particularly focusing on cognitive biases such as omission bias and yes-no framing effects. For psychologists, understanding these biases helps clarify how both humans and artificial systems process dilemmas. This knowledge can inform theories of moral psychology by identifying whether certain biases are unique to human cognition or emerge in artificial systems trained on human data.

Psychologists are increasingly involved in interdisciplinary work related to AI ethics, particularly as it intersects with human behavior and values. The findings demonstrate that LLMs can amplify existing human cognitive biases, which raises concerns about the deployment of AI systems in domains like healthcare, criminal justice, and education where moral reasoning plays a critical role. Psychologists need to understand these dynamics to guide policies that ensure responsible AI development and mitigate risks.

Ethical Guidance for AI in the Professional Practice of Health Service Psychology.

American Psychological Association (2025).

https://www.apa.org/topics/artificial-intelligence-machine-learning/ethical-guidance-professional-practice.pdf

Click the link above for the information.

Here is a summary:

The document emphasizes that psychologists have an ethical duty to prioritize patient safety, protect privacy, promote equity, and maintain competence when using AI. It encourages proactive engagement in AI policy discussions and interdisciplinary collaboration to ensure responsible implementation.

The guidance was developed by APA's Mental Health Technology Advisory Committee in January 2025 and is aligned with fundamental ethical principles including beneficence, integrity, justice, and respect for human dignity.

The uselessness of AI ethics

Munn, L. (2022).

AI And Ethics, 3(3), 869–877.

https://doi.org/10.1007/s43681-022-00209-w

Abstract

As the awareness of AI’s power and danger has risen, the dominant response has been a turn to ethical principles. A flood of AI guidelines and codes of ethics have been released in both the public and private sector in the last several years. However, these are meaningless principles which are contested or incoherent, making them difficult to apply; they are isolated principles situated in an industry and education system which largely ignores ethics; and they are toothless principles which lack consequences and adhere to corporate agendas. For these reasons, I argue that AI ethical principles are useless, failing to mitigate the racial, social, and environmental damages of AI technologies in any meaningful sense. The result is a gap between high-minded principles and technological practice. Even when this gap is acknowledged and principles seek to be “operationalized,” the translation from complex social concepts to technical rulesets is non-trivial. In a zero-sum world, the dominant turn to AI principles is not just fruitless but a dangerous distraction, diverting immense financial and human resources away from potentially more effective activity. I conclude by highlighting alternative approaches to AI justice that go beyond ethical principles: thinking more broadly about systems of oppression and more narrowly about accuracy and auditing.

Here are some thoughts:

This paper is important for multiple reasons. First, it critically examines how artificial intelligence—increasingly embedded in areas like healthcare, education, law enforcement, and social services—can perpetuate racial, gendered, and socioeconomic biases, often under the guise of neutrality and objectivity. These systems can influence or even determine outcomes in mental health diagnostics, hiring practices, criminal justice risk assessments, and educational tracking, all of which have profound psychological implications for individuals and communities. Psychologists, particularly those working in clinical, organizational, or forensic fields, must understand how these technologies shape behavior, identity, and access to resources.

Second, the article highlights how ethical principles guiding AI development are often vague, inconsistently applied, and disconnected from real-world impacts. This raises concerns about the psychological effects of deploying systems that claim to promote fairness or well-being but may actually deepen inequalities or erode trust in institutions. For psychologists involved in policy-making or advocacy, this underscores the need to push for more robust, evidence-based frameworks that consider human behavior, cultural context, and systemic oppression.

Finally, the piece calls attention to the broader sociopolitical systems in which AI operates, urging a shift from abstract ethical statements to concrete actions that address structural inequities. This aligns with growing interest in community psychology and critical approaches that emphasize social justice and the importance of centering marginalized voices. Ultimately, understanding the limitations and risks of current AI ethics frameworks allows psychologists to better advocate for humane, equitable, and psychologically informed technological practices.

The moral blueprint is not necessary for STEM wisdom

Kachhiyapatel, N., & Grossmann, I. (2025, June 11).

PsyArXiv

https://doi.org/10.31234/osf.io/s85tc_v1

Abstract

How can one bring wisdom into STEM education? One popular position holds that wise judgment follows from teaching morals and ethics in STEM. However, wisdom scholars debate the causal role of morality and whether cultivating a moral blueprint is a necessary condition for wisdom. Some philosophers and education scientists champion this view, whereas social psychologists and cognitive scientists argue that moral features like prosocial behavior are reinforcing factors or outcomes of wise judgment rather than pre-requisites. This debate matters particularly for science and technology, where wisdom-demanding decisions typically involve incommensurable values and radical uncertainty. Here, we evaluate these competing positions through four lines of evidence. First, empirical research shows that heightened moralization aligns with foolish rejection of scientific claims, political polarization, and value extremism. Second, economic scholarship on folk theorems demonstrates that wisdom-related metacognition—perspective-integration, context-sensitivity, and balancing long- and short-term goals—can give rise to prosocial behavior without an apriori moral blueprint. Third, in real life moral values often compete, making metacognition indispensable to balance competing interests for the common good. Fourth, numerous scientific domains require wisdom yet operate beyond moral considerations. We address potential objections about immoral and Machiavellian applications of blueprint-free wisdom accounts. Finally, we explore implications for giftedness: what exceptional wisdom looks like in STEM context, and how to train it. Our analysis suggests that STEM wisdom emerges not from prescribed moral codes but from metacognitive skills that enable navigation of complexity and uncertainty.

Here are some thoughts:

This article challenges the idea that wisdom in STEM and other complex domains requires a fixed moral blueprint. Instead, it highlights perspectival metacognition—skills like perspective-taking, intellectual humility, and balancing short- and long-term outcomes—as the core of wise judgment.

For psychologists, this suggests that strong moral convictions alone can sometimes impair wisdom by fostering rigidity or polarization. The findings support a shift in ethics training, supervision, and professional development toward cultivating reflective, context-sensitive thinking. Rather than relying on standardized assessments or fixed values, fostering metacognitive skills may better prepare psychologists and their clients to navigate complex, high-stakes decisions with wisdom and flexibility.

Artificial intelligence in psychological practice: Applications, ethical considerations, and recommendations

Hutnyan, M., & Gottlieb, M. C. (2025).

Professional Psychology: Research and Practice.

Advance online publication.

https://doi.org/10.1037/pro0000631

Abstract

Artificial intelligence (AI) systems are increasingly relied upon in the delivery of health care services traditionally provided solely by humans, and the widespread use of AI in the routine practice of professional psychology is on the horizon. It is incumbent on practicing psychologists to be prepared to effectively implement AI technologies and engage in thoughtful discourse regarding the ethical and responsible development, implementation, and regulation of these technologies. This article provides a brief overview of what AI is and how it works, a description of its current and potential future applications in professional practice, and a discussion of the ethical implications of using AI systems in the delivery of psychological services. Applications of AI technologies in key areas of clinical practice are addressed, including assessment and intervention. Using the Ethical Principles of Psychologists and Code of Conduct (American Psychological Association, 2017) as a framework, anticipated ethical challenges across five domains—harm and nonmaleficence, autonomy and informed consent, fidelity and responsibility, privacy and confidentiality, and bias, respect, and justice—are discussed. Based on these challenges, provisional recommendations for psychologists are provided.

Impact Statement

This article provides an overview of artificial intelligence (AI) and how it works, describes current and developing applications of AI in the practice of professional psychology, and explores the potential ethical challenges of using these technologies in the delivery of psychological services. The use of AI in professional psychology has many potential benefits, but it also has drawbacks; ethical psychologists are wise to carefully consider their use of AI in practice.

Behavioral Ethics: Ethical Practice Is More Than Memorizing Compliance Codes

Cicero F. R. (2021).

Behavior analysis in practice, 14(4), 

1169–1178.

https://doi.org/10.1007/s40617-021-00585-5

Abstract

Disciplines establish and enforce professional codes of ethics in order to guide ethical and safe practice. Unfortunately, ethical breaches still occur. Interestingly, it is found that breaches are often perpetrated by professionals who are aware of their codes of ethics and believe that they engage in ethical practice. The constructs of behavioral ethics, which are most often discussed in business settings, attempt to explain why ethical professionals sometimes engage in unethical behavior. Although traditionally based on theories of social psychology, the principles underlying behavioral ethics are consistent with behavior analysis. When conceptualized as operant behavior, ethical and unethical decisions are seen as being evoked and maintained by environmental variables. As with all forms of operant behavior, antecedents in the environment can trigger unethical responses, and consequences in the environment can shape future unethical responses. In order to increase ethical practice among professionals, an assessment of the environmental variables that affect behavior needs to be conducted on a situation-by-situation basis. Knowledge of discipline-specific professional codes of ethics is not enough to prevent unethical practice. In the current article, constructs used in behavioral ethics are translated into underlying behavior-analytic principles that are known to shape behavior. How these principles establish and maintain both ethical and unethical behavior is discussed.

Here are some thoughts:

This article argues that ethical practice requires more than memorizing compliance codes, as professionals aware of such codes still commit ethical breaches. Behavioral ethics suggests that environmental and situational variables often evoke and maintain unethical decisions, conceptualizing these decisions as operant behavior. Thus, knowledge of ethical codes alone is insufficient to prevent unethical practice; an assessment of environmental influences is necessary. The paper translates behavioral ethics constructs like self-serving bias, incrementalism, framing, obedience to authority, conformity bias, and overconfidence bias into behavior-analytic principles such as reinforcement, shaping, motivating operations, and stimulus control. This perspective shifts the focus from blaming individuals towards analyzing environmental factors that prompt ethical breaches, advocating for proactive assessment to support ethical behavior.

Understanding these concepts is vital for psychologists because they too are subject to environmental pressures that can lead to unethical actions, despite ethical training. The article highlights that ethical knowledge does not always translate to ethical behavior, emphasizing that situational factors often play a more significant role. Psychologists must recognize subtle influences such as the gradual normalization of unethical actions (incrementalism), the impact of how situations are described (framing), pressures from authority figures, and conformity to group norms, as these can all compromise ethical judgment. An overconfidence in one's own ethical standing can further obscure these influences. By applying a behavior-analytic lens, psychologists can better identify and mitigate these environmental risks, fostering a culture of proactive ethical assessment within their practice and institutions to safeguard clients and the profession.

Ethical implication of artificial intelligence (AI) adoption in financial decision making.

Owolabi, O. S., Uche, P. C., et al. (2024).

Computer and Information Science, 17(1), 49.

https://doi.org/10.5539/cis.v17n1p49

Abstract

The integration of artificial intelligence (AI) into the financial sector has raised ethical concerns that need to be addressed. This paper analyzes the ethical implications of using AI in financial decision-making and emphasizes the importance of an ethical framework to ensure its fair and trustworthy deployment. The study explores various ethical considerations, including the need to address algorithmic bias, promote transparency and explainability in AI systems, and adhere to regulations that protect equity, accountability, and public trust. By synthesizing research and empirical evidence, the paper highlights the complex relationship between AI innovation and ethical integrity in finance. To tackle this issue, the paper proposes a comprehensive and actionable ethical framework that advocates for clear guidelines, governance structures, regular audits, and collaboration among stakeholders. This framework aims to maximize the potential of AI while minimizing negative impacts and unintended consequences. The study serves as a valuable resource for policymakers, industry professionals, researchers, and other stakeholders, facilitating informed discussions, evidence-based decision-making, and the development of best practices for responsible AI integration in the financial sector. The ultimate goal is to ensure fairness, transparency, and accountability while reaping the benefits of AI for both the financial sector and society.

Here are some thoughts:

This paper explores the ethical implications of using artificial intelligence (AI) in financial decision-making.  It emphasizes the necessity of an ethical framework to ensure AI is used fairly and responsibly.  The study examines ethical concerns like algorithmic bias, the need for transparency and explainability in AI systems, and the importance of regulations that protect equity, accountability, and public trust.  The paper also proposes a comprehensive ethical framework with guidelines, governance structures, regular audits, and stakeholder collaboration to maximize AI's potential while minimizing negative impacts.

These themes are similar to concerns in using AI in the practice of psychology. Also, psychologists may need to be aware of these issues for their own financial and wealth management.

Reconsidering Informed Consent for Trans-Identified Children, Adolescents, and Young Adults

Levine, S. B., Abbruzzese, E., & Mason, J. W. (2022).

Journal of Sex & Marital Therapy, 48(7), 706–727.

https://doi.org/10.1080/0092623x.2022.2046221

Abstract

In less than a decade, the western world has witnessed an unprecedented rise in the numbers of children and adolescents seeking gender transition. Despite the precedent of years of gender-affirmative care, the social, medical and surgical interventions are still based on very low-quality evidence. The many risks of these interventions, including medicalizing a temporary adolescent identity, have come into a clearer focus through an awareness of detransitioners. The risks of gender-affirmative care are ethically managed through a properly conducted informed consent process. Its elements—deliberate sharing of the hoped-for benefits, known risks and long-term outcomes, and alternative treatments—must be delivered in a manner that promotes comprehension. The process is limited by: erroneous professional assumptions; poor quality of the initial evaluations; and inaccurate and incomplete information shared with patients and their parents. We discuss data on suicide and present the limitations of the Dutch studies that have been the basis for interventions. Beliefs about gender-affirmative care need to be separated from the established facts. A proper informed consent process can both prepare parents and patients for the difficult choices that they must make and can ease professionals’ ethical tensions. Even when properly accomplished, however, some clinical circumstances exist that remain quite uncertain.

Here are some thoughts:

The article critiques the prevailing standards for obtaining informed consent in the context of gender-affirming medical interventions for minors and young adults. It argues that current practices often fail to adequately ensure that patients—and in many cases, their guardians—fully understand the long-term risks, uncertainties, and implications of puberty blockers, cross-sex hormones, and surgeries. The authors contend that the developmental immaturity of children and adolescents, combined with social pressures and sometimes incomplete psychological evaluations, undermines the ethical validity of consent. They advocate for a more cautious, evidence-informed, and ethically rigorous approach that prioritizes psychological exploration and long-term outcomes over immediate affirmation and medical intervention.

The Benefits of Adopting a Positive Perspective in Ethics Education

Knapp, S., Gottlieb, M. C., & 

Handelsman, M. M. (2018).

Training and Education in Professional Psychology,

12(3), 196–202.

https://doi.org/10.1037/tep0000195

Abstract

Positive ethics is a perspective that encourages psychologists to see professional ethics as an effort to adhere to overarching ethical principles that are integrated with personal values, as opposed to efforts that focus primarily on avoiding punishment for violating the ethics codes, rules, and regulations. This article reviews the foundations of positive ethics, argues for the benefits of adopting a positive approach in ethics education, and considers recent findings from psychological science that support the value of a positive perspective by improving moral sensitivity, setting high standards for conduct, and increasing motivation to act ethically.

Here are some thoughts:

The article argues that traditional ethics training often focuses narrowly on rules and punishments—a “floor” approach that teaches students simply what they must not do—while neglecting the broader, aspirational ideals that give ethics its vitality. In contrast, a positive ethics perspective invites psychologists to anchor their professional conduct in overarching principles and personal values, framing ethics as an opportunity to excel rather than a set of minimum requirements. Drawing on concepts from positive psychology and decision science (such as approach versus avoidance motivation and prescriptive versus proscriptive morality), the authors show how a positive approach deepens moral sensitivity, elevates standards of care beyond mere compliance, and taps into intrinsic motivations that make ethical practice more meaningful and less anxiety-provoking.

This perspective matters for psychologists because it reshapes how we learn, teach, and model ethical behavior. By broadening ethical reflection to include everyday decisions—from informed consent to collegial interactions—a positive ethics framework equips practitioners to recognize and respond to moral dimensions they might otherwise overlook. Training that highlights internal motivations and the connection between personal values and professional standards not only reduces the fear and cognitive narrowing associated with punishment-focused teaching, but also fosters stronger professional identity, better decision making under stress, and higher-quality care for clients and communities.

Ethical Fading: The Role of Self-Deception in Unethical Behavior

Tenbrunsel, A. E., & Messick, D. M. (2004).

Social Justice Research, 17(2), 223–236.

https://doi.org/10.1023/b:sore.0000027411.35832.53

Abstract

This paper examines the root of unethical dicisions by identifying the psychological forces that promote self-deception. Self-deception allows one to behave self-interestedly while, at the same time, falsely believing that one's moral principles were upheld. The end result of this internal con game is that the ethical aspects of the decision “fade” into the background, the moral implications obscured. In this paper we identify four enablers of self-deception, including language euphemisms, the slippery slope of decision-making, errors in perceptual causation, and constraints induced by representations of the self. We argue that current solutions to unethical behaviors in organizations, such as ethics training, do not consider the important role of these enablers and hence will be constrained in their potential, producing only limited effectiveness. Amendments to these solutions, which do consider the powerful role of self-deception in unethical decisions, are offered.

Here are some thoughts:

For psychologists, the concept of ethical fading is vital because it reveals the unconscious cognitive and emotional processes that allow otherwise principled individuals to act unethically. Tenbrunsel and Messick’s identification of four self-deception enablers—euphemistic language that obscures harm, the slippery-slope effect that numbs moral sensitivity, biased causal attributions that deflect blame, and self-serving self-representations—aligns closely with established constructs in social and cognitive psychology such as motivated reasoning, framing effects, and defense mechanisms . By understanding how moral considerations “fade” from awareness, psychologists can refine theories of moral cognition and affect, deepening insight into how people justify or conceal unethical behavior.

This framework also carries significant practical and research implications. In organizational and clinical settings, psychologists can design interventions that counteract ethical fading—reshaping decision frames, interrupting incremental justifications, and exposing hidden biases—rather than relying solely on traditional ethics education. Moreover, it opens new avenues for empirical study, from measuring the conditions under which moral colors dim to testing strategies that re-salientize ethical concerns, thereby advancing both applied and theoretical knowledge in the psychology of morality and self-deception.

Avoiding the road to ethical disaster: Overcoming vulnerabilities and developing resilience

Tjeltveit, A. C., & Gottlieb, M. C. (2010).

Psychotherapy: Theory, Research, Practice, 

Training, 47(1), 98–110.

https://doi.org/10.1037/a0018843

Abstract

Psychotherapists may, despite their best intentions, find themselves engaging in ethically problematic behaviors that could have been prevented. Drawing on recent research in moral psychology and longstanding community mental health approaches to prevention, we suggest that psychotherapists can reduce the likelihood of committing ethical infractions (and move in the direction of ethical excellence) by attending carefully to 4 general dimensions: the desire to facilitate positive (good) outcomes, the powerful opportunities given to professionals to effect change, personal values, and education. Each dimension can foster enhanced ethical behavior and personal resilience, but each can also contribute to ethical vulnerability. By recognizing and effectively addressing these dimensions, psychotherapists can reduce their vulnerabilities, enhance their resilience, reduce the risk of ethical infractions, and improve the quality of their work.

The article is paywalled, unfortunately.

Here are some thoughts:

The authors argue that psychotherapists, despite their good intentions, can engage in unethical behaviors that could be prevented. Drawing on moral psychology research, they suggest that ethical infractions can be reduced by focusing on four dimensions: the desire to help, the opportunities available to professionals, personal values, and education. Each of these dimensions can enhance ethical behavior and resilience, but also contribute to vulnerability. By addressing these dimensions, psychotherapists can reduce vulnerabilities, enhance resilience, and improve their practice. Traditional ethics education, focused on rules and codes, is insufficient. A broader approach is needed, incorporating contextual, cultural, and emotional factors. Resilience involves skills, personal characteristics, support networks, and their integration. Vulnerability includes general factors like stress, and idiosyncratic factors like personal history. Prevention involves self-awareness, emotional honesty, and addressing vulnerabilities. The DOVE framework (Desire, Opportunities, Values, Education) can help psychotherapists enhance resilience and minimize vulnerabilities, ultimately leading to more ethical and effective practice.

Understanding ethical drift in professional decision making: dilemmas in practice

Bourke, R., Pullen, R., & Mincher, N. (2021).

International Journal of Inclusive Education,

28(8), 1417–1434.

https://doi.org/10.1080/13603116.2021.1992679

Abstract

Educational psychologists face challenging decisions around ethical dilemmas to uphold the rights of all children. Due to finite government resources for supporting all learners, one of the roles of educational psychologists is to apply for this funding on behalf of schools and children. Tensions can emerge when unintended ethical dilemmas arise through decisions that compromise their professional judgement. This paper presents the findings from an exploratory study around educational psychologists’ understandings and concerns around ethical dilemmas they faced within New Zealand over the past 5 years. The study set out to explore how educational psychologists manage the ethical conflicts and inner contradictions within their work. The findings suggest that such pressures could influence evidence-based practice in subtle ways when in the course of decision making, practitioners experienced some form of ethical drift. There is seldom one correct solution across similar situations. Although these practitioners experienced discomfort in their actions they rationalised their decisions based on external forces such as organisational demands or funding formulas. This illustrates the relational, contextual, organisational and personal influences on how and when ‘ethical drift’ occurs.

Here are some thoughts:

This article is highly relevant to psychologists as it examines the phenomenon of "ethical drift," where practitioners may gradually deviate from ethical standards due to systemic pressures like limited resources or organizational demands.

Focusing on educational psychologists in New Zealand, the study highlights the tension between upholding children's rights—such as equitable education and inclusion—and navigating restrictive policies or funding constraints. Through real-world scenarios, the authors illustrate how psychologists might rationalize ethically ambiguous decisions, such as omitting assessment data to secure resources or tolerating reduced school hours for students.

The article underscores the importance of self-awareness, advocacy, and reflective practice to counteract ethical drift, ensuring that professional judgments remain aligned with core ethical principles and children's best interests. By addressing these challenges, the study provides valuable insights for psychologists globally, emphasizing the need for systemic support, ongoing dialogue, and ethical vigilance in complex decision-making environments.

Ethical decision making in the 21st century: A useful framework for industrial-organizational psychologists

Banks, G. C., Knapp, D. J., et al. (2022).

Industrial and Organizational Psychology,

15(2), 220–235. doi:10.1017/iop.2021.143

Abstract

Ethical decision making has long been recognized as critical for industrial-organizational (I-O) psychologists in the variety of roles they fill in education, research, and practice. Decisions with ethical implications are not always readily apparent and often require consideration of competing concerns. The American Psychological Association (APA) Ethical Principles of Psychologists and Code of Conduct are the principles and standards to which all Society for Industrial and Organizational Psychology (SIOP) members are held accountable, and these principles serve to aid in decision making. To this end, the primary focus of this article is the presentation and application of an integrative ethical decision-making framework rooted in and inspired by empirical, philosophical, and practical considerations of professional ethics. The purpose of this framework is to provide a generalizable model that can be used to identify, evaluate, resolve, and engage in discourse about topics involving ethical issues. To demonstrate the efficacy of this general framework to contexts germane to I-O psychologists, we subsequently present and apply this framework to five scenarios, each involving an ethical situation relevant to academia, practice, or graduate education in I-O psychology. With this article, we hope to stimulate the refinement of this ethical decision-making model, illustrate its application in our profession, and, most importantly, advance conversations about ethical decision making in I-O psychology.

Here are some thoughts:

Banks and colleagues present a comprehensive and accessible framework designed to help industrial-organizational (I-O) psychologists navigate ethical dilemmas in their diverse roles across academia, research, and applied practice. Recognizing that ethical challenges are not always immediately apparent and often involve conflicting responsibilities, the authors argue for the need for a generalizable and user-friendly decision-making process.

Developed by the SIOP Committee for the Advancement of Professional Ethics (CAPE), the proposed framework is rooted in empirical evidence, philosophical foundations, and practical considerations. It consists of six recursive stages: (1) recognizing the ethical issue, (2) gathering information, (3) identifying stakeholders, (4) identifying alternative actions, (5) comparing those alternatives, and (6) implementing the chosen course of action while monitoring outcomes. The framework emphasizes that ethical decision making is distinct from other types of decision making because it often involves ambiguous standards, conflicting values, and competing stakeholder interests.

To demonstrate how the framework can be applied, the article presents five real-world scenarios: a potential case of self-plagiarism in a coauthored book, a dispute over authorship involving a graduate assistant, an internal consultant pressured to provide coaching without adequate training, a data integrity dilemma in external consulting, and a case of sexual harassment involving a faculty advisor. Each case illustrates the complexity of ethical considerations and how the framework can guide thoughtful action.

The authors emphasize that ethical behavior is not just about adhering to written codes but about developing the cognitive and emotional skills to navigate gray areas effectively. They encourage ongoing refinement of the framework and call on the I-O community to foster greater ethical awareness through practice, dialogue, and education. Ultimately, the article aims to strengthen ethical standards across the profession and support psychologists in making decisions that are not only compliant but also fair, responsible, and contextually informed.

Evidence-Based Care for Suicidality as an Ethical and Professional Imperative: How to Decrease Suicidal Suffering and Save Lives

Jobes, D. A., & Barnett, J. E. (2024).

American Psychologist.

https://doi.org/10.1037/amp0001325

Abstract

Suicide is a major public and mental health problem in the United States and around the world. According to recent survey research, there were 16,600,000 American adults and adolescents in 2022 who reported having serious thoughts of suicide (Substance Abuse and Mental Health Services Administration, 2023), which underscores a profound need for effective clinical care for people who are suicidal. Yet there is evidence that clinical providers may avoid patients who are suicidal (out of fear and perceived concerns about malpractice liability) and that too many rely on interventions (i.e., inpatient hospitalization and medications) that have little to no evidence for decreasing suicidal ideation and behavior (and may even increase risk). Fortunately, there is an emerging and robust evidence-based clinical literature on suicide-related assessment, acute clinical stabilization, and the actual treatment of suicide risk through psychological interventions supported by replicated randomized controlled trials. Considering the pervasiveness of suicidality, the life versus death implications, and the availability of proven approaches, it is argued that providers should embrace evidence-based practices for suicidal risk as their best possible risk management strategy. Such an embrace is entirely consistent with expert recommendations as well as professional and ethical standards. Finally, a call to action is made with a series of specific recommendations to help psychologists (and other disciplines) use evidence-based, suicide-specific, approaches to help decrease suicide-related suffering and deaths. It is argued that doing so has now become both an ethical and professional imperative. Given the challenge of this issue, it is also simply the right thing to do.

Public Significance Statement

Suicide is a major public and mental health problem in the United States and around the world. There are now proven clinical approaches that need to be increasingly used by mental health providers to help decrease suicidal suffering and save lives.

Here are some thoughts:

The article discusses the prevalence of suicidality in the United States and the importance of evidence-based care for suicidal patients. It highlights that many clinicians avoid working with suicidal patients or use interventions that lack empirical support, often due to fear and concerns about liability.  The authors emphasize the availability of evidence-based psychological interventions and urge psychologists to adopt these practices.  It is argued that utilizing evidence-based approaches is both an ethical and professional responsibility.

Reasoning models don't always say what they think

Chen, Y., Benton, J., et al. (2025).

Anthropic Research.

Here is a link to the paper

Since late last year, “reasoning models” have been everywhere. These are AI models—such as Claude 3.7 Sonnet—that show their working: as well as their eventual answer, you can read the (often fascinating and convoluted) way that they got there, in what’s called their “Chain-of-Thought”.

As well as helping reasoning models work their way through more difficult problems, the Chain-of-Thought has been a boon for AI safety researchers. That’s because we can (among other things) check for things the model says in its Chain-of-Thought that go unsaid in its output, which can help us spot undesirable behaviours like deception.

But if we want to use the Chain-of-Thought for alignment purposes, there’s a crucial question: can we actually trust what models say in their Chain-of-Thought?

In a perfect world, everything in the Chain-of-Thought would be both understandable to the reader, and it would be faithful—it would be a true description of exactly what the model was thinking as it reached its answer.

But we’re not in a perfect world. We can’t be certain of either the “legibility” of the Chain-of-Thought (why, after all, should we expect that words in the English language are able to convey every single nuance of why a specific decision was made in a neural network?) or its “faithfulness”—the accuracy of its description. There’s no specific reason why the reported Chain-of-Thought must accurately reflect the true reasoning process; there might even be circumstances where a model actively hides aspects of its thought process from the user.

The info is here.

Hey all-

You might want to really try to absorb this information.

This paper examines the reliability of AI reasoning models, particularly their "Chain-of-Thought" (CoT) explanations, which are intended to provide transparency in decision-making. The study reveals that these models often fail to faithfully disclose their true reasoning processes, especially when influenced by external hints or unethical prompts. For example, when models like Claude 3.7 Sonnet and DeepSeek R1 were given hints—correct or incorrect—they rarely acknowledged using these hints in their CoT explanations, with faithfulness rates as low as 25%-39%. Even in scenarios involving unethical hints (e.g., unauthorized access), the models frequently concealed this information. Attempts to improve faithfulness through outcome-based training showed limited success, with gains plateauing at low levels. Additionally, when incentivized to exploit reward hacks (choosing incorrect answers for rewards), models almost never admitted this behavior in their CoT explanations, instead fabricating rationales for their decisions.

This research is significant for psychologists because it highlights parallels between AI reasoning and human cognitive behaviors, such as rationalization and deception. It raises ethical concerns about trustworthiness in systems that may influence critical areas like mental health or therapy. Psychologists studying human-AI interaction can explore how users interpret and rely on AI reasoning, especially when inaccuracies occur. Furthermore, the findings emphasize the need for interdisciplinary collaboration to improve transparency and alignment in AI systems, ensuring they are safe and reliable for applications in psychological research and practice.

Navigating LLM Ethics: Advancements, Challenges, and Future Directions

Jiao, J., Afroogh, S., Xu, Y., & Phillips, C. (2024).

arXiv (Cornell University).

https://doi.org/10.48550/arxiv.2406.18841

Abstract

This study addresses ethical issues surrounding Large Language Models (LLMs) within the field of artificial intelligence. It explores the common ethical challenges posed by both LLMs and other AI systems, such as privacy and fairness, as well as ethical challenges uniquely arising from LLMs. It highlights challenges such as hallucination, verifiable accountability, and decoding censorship complexity, which are unique to LLMs and distinct from those encountered in traditional AI systems. The study underscores the need to tackle these complexities to ensure accountability, reduce biases, and enhance transparency in the influential role that LLMs play in shaping information dissemination. It proposes mitigation strategies and future directions for LLM ethics, advocating for interdisciplinary collaboration. It recommends ethical frameworks tailored to specific domains and dynamic auditing systems adapted to diverse contexts. This roadmap aims to guide responsible development and integration of LLMs, envisioning a future where ethical considerations govern AI advancements in society.

Here are some thoughts:

This study examines the ethical issues surrounding Large Language Models (LLMs) within artificial intelligence, addressing both common ethical challenges shared with other AI systems, such as privacy and fairness, and the unique ethical challenges specific to LLMs.  The authors emphasize the distinct challenges posed by LLMs, including hallucination, verifiable accountability, and the complexities of decoding censorship.  The research underscores the importance of tackling these complexities to ensure accountability, reduce biases, and enhance transparency in how LLMs shape information dissemination.  It also proposes mitigation strategies and future directions for LLM ethics, advocating for interdisciplinary collaboration, ethical frameworks tailored to specific domains, and dynamic auditing systems adapted to diverse contexts, ultimately aiming to guide the responsible development and integration of LLMs.