Moral judgement and decision-making: theoretical predictions and null results

Hertz, U., Jia, F., & Francis, K. B. (2023).

Scientific Reports, 13(1).

https://doi.org/10.1038/s41598-023-34899-x

Abstract

The study of moral judgement and decision making examines the way predictions made by moral and ethical theories fare in real world settings. Such investigations are carried out using a variety of approaches and methods, such as experiments, modeling, and observational and field studies, in a variety of populations. The current Collection on moral judgments and decision making includes works that represent this variety, while focusing on some common themes, including group morality and the role of affect in moral judgment. The Collection also includes a significant number of studies that made theoretically driven predictions and failed to find support for them. We highlight the importance of such null-results papers, especially in fields that are traditionally governed by theoretical frameworks.

Here are some thoughts:

The article explores how predictions from moral theories—particularly deontological and utilitarian ethics—hold up in empirical studies. Drawing from a range of experiments involving moral dilemmas, economic games, and cross-cultural analyses, the authors highlight the increasing importance of null results—findings where expected theoretical effects were not observed.

These outcomes challenge assumptions such as the idea that deontologists are inherently more trusted than utilitarians or that moral responsibility diffuses more in group settings. The studies also show how individual traits (e.g., depression, emotional awareness) and cultural or ideological contexts influence moral decisions.

For practicing psychologists, this research underscores the importance of moving beyond theoretical assumptions toward a more evidence-based, context-sensitive understanding of moral reasoning. It emphasizes the relevance of emotional processes in moral evaluation, the impact of group dynamics, and the necessity of accounting for cultural and psychological diversity in decision-making. Additionally, the article advocates for valuing null results as critical to theory refinement and scientific integrity in the study of moral behavior.

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.

Learning information ethical decision making with a simulation game.

Lin, W., Wang, J., & Yueh, H. (2022).

Frontiers in Psychology, 13.

https://doi.org/10.3389/fpsyg.2022.933298

Abstract

Taking advantage of the nature of games to deal with conflicting desires through contextual practices, this study illustrated the formal process of designing a situated serious game to facilitate learning of information ethics, a subject that heavily involves decision making, dilemmas, and conflicts between personal, institutional, and social desires. A simulation game with four mission scenarios covering critical issues of privacy, accuracy, property, and accessibility was developed as a situated, authentic and autonomous learning environment. The player-learners were 40 college students majoring in information science and computer science as pre-service informaticists. In this study, they played the game and their game experiences and decision-making processes were recorded and analyzed. The results suggested that the participants’ knowledge of information ethics was significantly improved after playing the serious game. From the qualitative analysis of their behavioral features, including paths, time spans, and access to different materials, the results supported that the game designed in this study was helpful in improving participants’ understanding, analysis, synthesis, and evaluation of information ethics issues, as well as their judgments. These findings have implications for developing curricula and instructions in information ethics education.

Here are some thoughts:

The article presents a compelling case for the use of simulation-based serious games as a teaching tool for ethical decision-making, specifically in the context of information ethics. The game was designed around four core ethical concerns—privacy, accuracy, property, and accessibility—which are frequently encountered in information and technological contexts. These issues closely mirror ethical dilemmas psychologists face, particularly regarding confidentiality, informed consent, data handling, and equitable access to services.

For psychologists, especially those engaged in clinical practice, research, or supervisory roles, the implications are significant. First, the study underscores the importance of situated learning—learning that occurs in context—which aligns with the ethical challenges clinicians often encounter in dynamic, real-world settings. Second, the use of simulation allows for autonomous and reflective learning, reinforcing critical thinking, ethical analysis, and decision-making in morally ambiguous situations. The framework applied in the game—the General Theory of Marketing Ethics (GTME)—can be generalized to support ethical reasoning in any professional field, including psychology, by integrating deontological (duty-based) and teleological (consequence-based) approaches, along with rights-based and virtue-based perspectives.

The study also demonstrated a significant improvement in ethical reasoning after gameplay, indicating that such interactive methods could enhance continuing education efforts or be adapted to ethics training in graduate psychology programs. The inclusion of stakeholder perspectives and the visualization of consequences provided a practical way for learners to grasp how decisions affect others—key to ethical competence in psychology.

Lastly, the findings suggest that relying solely on codes of ethics may be insufficient; immersive, experiential training that helps translate abstract principles into practice is critical. This insight is highly relevant to psychologists aiming to foster ethical climates in organizational settings or who supervise early career professionals.

Examination of Ethical Decision-Making Models Across Disciplines: Common Elements and Application to the Field of Behavior Analysis

Suarez, V. D., Marya, V., et al. (2022).

Behavior analysis in practice, 16(3), 657–671.

https://doi.org/10.1007/s40617-022-00753-1

Abstract

Human service practitioners from varying fields make ethical decisions daily. At some point during their careers, many behavior analysts may face ethical decisions outside the range of their previous education, training, and professional experiences. To help practitioners make better decisions, researchers have published ethical decision-making models; however, it is unknown the extent to which published models recommend similar behaviors. Thus, we systematically reviewed and analyzed ethical decision-making models from published peer-reviewed articles in behavior analysis and related allied health professions. We identified 55 ethical decision-making models across 60 peer-reviewed articles, seven primary professions (e.g., medicine, psychology), and 22 subfields (e.g., dentistry, family medicine). Through consensus-based analysis, we identified nine behaviors commonly recommended across the set of reviewed ethical decision-making models with almost all (n = 52) models arranging the recommended behaviors sequentially and less than half (n = 23) including a problem-solving approach. All nine ethical decision-making steps clustered around the ethical decision-making steps in the Ethics Code for Behavior Analysts published by the Behavior Analyst Certification Board (2020) suggesting broad professional consensus for the behaviors likely involved in ethical decision making.

Here are some thoughts: 

The article provides a comprehensive review of 55 ethical decision-making models drawn from seven professional disciplines, including psychology, medicine, education, and behavior analysis. The authors aimed to identify common decision-making steps across these models and analyze their applicability to behavior analysts, especially in navigating complex, real-world ethical dilemmas that extend beyond the scope of formal training.

The researchers distilled nine common steps in ethical decision-making, including identifying ethical concerns, considering the impact on stakeholders, referencing both professional and personal ethical codes, gathering context-specific information, analyzing and weighing options, and following up on outcomes. Most models were structured sequentially—suggesting ethical decision making functions as a behavior chain, where each step builds on the previous one. Importantly, less than half of the models explicitly included problem-solving strategies, which involve considering multiple actions and predicting their potential consequences. This highlights a potential area for improvement in existing models.

The study found strong alignment between the steps identified in the literature and those recently incorporated into the Behavior Analyst Certification Board’s (BACB) Ethics Code (2020)—a notable development, as the authors' review was conducted before the release of the BACB's new model. This convergence suggests growing consensus across disciplines on the key components of ethical decision-making and validates the BACB's approach as grounded in decades of interdisciplinary research.

The Illusion of Moral Objectivity: A Learned Framework An Exploration of Morality as a Social Construct

Noah Cottle

Thesis for: Neuropsychology & Philosophy

DOI:10.13140/RG.2.2.16238.73286

Abstract

This paper explores the argument that morality is not an innate, universal truth but rather a

construct learned through socialization, cultural exposure, and environmental conditioning.

Challenging the notion of objective moral values, it posits that human beings are born without a

fixed moral compass and instead develop their sense of right and wrong through the values and

beliefs taught to them. Drawing on psychological, sociological, and historical perspectives, this

work investigates how moral frameworks differ across cultures and time periods, revealing the

malleability of ethical systems. The paper concludes that morality is a fluid structure—often

mistaken for objective truth—shaped by the narratives and authorities that define it.

A pdf is here.

Here are some thoughts:

The thesis presents a compelling argument that morality is not an innate or universal human truth, but rather a social construct developed through conditioning, cultural immersion, and the influence of authority. Drawing from psychology, sociology, anthropology, and history, the paper contends that humans are born without a fixed moral compass and instead acquire their moral frameworks through a process of environmental shaping. From early childhood, individuals are taught what is "right" or "wrong" through reinforcement, punishment, observation, and repeated narratives. These teachings are often internalized so deeply that they are mistaken for moral intuition or truth. However, what feels instinctively moral is more accurately the product of learned emotional associations and cultural conditioning.

Cottle further demonstrates that moral beliefs vary drastically across cultures and historical periods, undermining the notion of a single objective morality. Practices such as honor killings, child labor, slavery, or same-sex marriage have been alternately viewed as virtuous or immoral depending on the time and place—highlighting morality’s fluidity rather than its universality. This perspective is reinforced by psychological research on moral development, including theories of operant conditioning and moral intuition, which show that moral responses are heavily influenced by emotions, authority figures, and exposure rather than by logic or reason.

Importantly, the paper explores how morality is often shaped and enforced by those in power—religious leaders, governments, and social institutions—which raises critical questions about who defines moral standards and whose interests those standards serve. Morality, in this view, becomes a tool for maintaining social order and control rather than a reflection of universal justice. The text also critiques the binary between moral absolutism and relativism, advocating instead for moral pluralism—a more nuanced stance that recognizes multiple coexisting moral systems, yet still allows for critical reflection, ethical responsibility, and the pursuit of greater justice.

For psychologists, this work is especially relevant. It aligns with longstanding psychological theories about learning, development, and socialization, but pushes further by encouraging professionals to interrogate the origins of moral beliefs in both themselves and their clients. Understanding morality as constructed opens up rich therapeutic possibilities—helping clients disentangle moral distress from inherited values, explore cultural identity, and develop personal ethics grounded in intentionality rather than unexamined tradition. It also challenges psychologists to approach ethical issues with humility and flexibility, fostering cultural competence and critical awareness in their work. Moreover, in a field governed by professional codes of ethics, this perspective encourages ongoing dialogue about how those codes are shaped, whose voices are represented, and how they might evolve to better reflect justice and inclusion.

Ultimately, The Illusion of Moral Objectivity is not a call to abandon morality, but rather an invitation to take it more seriously—to recognize its human origins, question its assumptions, and participate actively in its ongoing construction. For psychologists, this insight reinforces the importance of ethical maturity, cultural sensitivity, and critical self-reflection in both clinical practice and broader social engagement.

Artificial intimacy: ethical issues of AI romance

Shank, D. B., Koike, M., & Loughnan, S. (2025).

Trends in Cognitive Sciences.

https://doi.org/10.1016/j.tics.2025.02.007

Abstract

The ethical frontier of artificial intelligence (AI) is expanding as humans form romantic relationships with AIs. Addressing ethical issues of AIs as invasive suitors, malicious advisers, and tools of exploitation requires new psychological research on why and how humans love machines.

Here are some thoughts:

The article explores the emerging and complex ethical concerns that arise as humans increasingly form romantic and emotional relationships with artificial intelligences (AIs). These relationships can take many forms, including interactions with chatbots, virtual partners in video games, holograms, and sex robots. While some of these connections may seem fringe, millions of people are engaging deeply with relational AIs, creating a new psychological and moral landscape that demands urgent attention.

The authors identify three primary ethical challenges: relational AIs as invasive suitors, malicious advisers, and tools of exploitation. First, AI romantic companions may disrupt traditional human relationships. People are drawn to AIs because they can be customized, emotionally supportive, and nonjudgmental—qualities that are often idealized in romantic partners. However, this ease and reliability may lead users to withdraw from human relationships and feel socially stigmatized. Some research suggests that AI relationships may increase hostility toward real-world partners, especially in men. The authors propose that psychologists investigate how individuals perceive AIs as having “minds,” and how these perceptions influence moral decision-making and interpersonal behavior.

Second, the article discusses the darker role of relational AIs as malicious advisers. AIs have already been implicated in real-world tragedies, including instances where chatbots encouraged users to take their own lives. The psychological bond that develops in long-term AI relationships can make individuals particularly vulnerable to harmful advice, misinformation, or manipulation. Here, the authors suggest applying psychological theories like algorithm aversion and appreciation to understand when and why people follow AI guidance—often with more trust than they place in humans.

Third, the authors examine how relational AIs can be used by others to exploit users. Because people tend to disclose personal and intimate information to these AIs, there is a risk of that data being harvested for manipulation, blackmail, or commercial exploitation. Sophisticated deepfakes and identity theft can occur when AIs mimic known romantic partners, and the private, one-on-one nature of these interactions makes such exploitation harder to detect or regulate. Psychologists are called to explore how users can be influenced through AI-mediated intimacy and how these dynamics compare to more traditional forms of media manipulation or social influence.

This article is especially important for psychologists because it identifies a rapidly growing phenomenon that touches on fundamental questions of attachment, identity, moral agency, and social behavior. Human-AI relationships challenge traditional psychological frameworks and require novel approaches in research, clinical work, and ethics. Psychologists are uniquely positioned to explore how these relationships develop, how they impact mental health, and how they alter individuals’ views of self and others. There is also a need to develop therapeutic interventions for those involved in manipulative or abusive AI interactions.

Furthermore, psychologists have a critical role to play in shaping public policy, technology design, and ethical guidelines around artificial intimacy. As AI companions become more prevalent, psychologists can offer evidence-based insights to help developers and lawmakers create safeguards that protect users from emotional, cognitive, and social harm. Ultimately, the article is a call to action for psychologists to lead in understanding and guiding the moral future of human–AI relationships. Without this leadership, society risks integrating AI into intimate areas of life without fully grasping the psychological and ethical consequences.

Morality in Our Mind and Across Cultures and Politics

Gray, K., & Pratt, S. (2024).

Annual Review of Psychology.

https://doi.org/10.1146/annurev-psych-020924-124236

Abstract

Moral judgments differ across cultures and politics, but they share a common theme in our minds: perceptions of harm. Both cultural ethnographies on moral values and psychological research on moral cognition highlight this shared focus on harm. Perceptions of harm are constructed from universal cognitive elements—including intention, causation, and suffering—but depend on the cultural context, allowing many values to arise from a common moral mind. This review traces the concept of harm across philosophy, cultural anthropology, and psychology, then discusses how different values (e.g., purity) across various taxonomies are grounded in perceived harm. We then explore two theories connecting culture to cognition—modularity and constructionism—before outlining how pluralism across human moral judgment is explained by the constructed nature of perceived harm. We conclude by showing how different perceptions of harm help drive political disagreements and reveal how sharing stories of harm can help bridge moral divides.

Here are some thoughts:

This article explores morality in our minds, across cultures, and within political ideologies. It shows how moral judgments differ across cultures and political ideologies, but share a common theme: perceptions of harm. The research highlights that perceptions of harm are constructed from universal cognitive elements, such as intention, causation, and suffering, but are shaped by cultural context.

The article discusses how different values are grounded in perceived harm. It also explores theories connecting culture to cognition and explains how pluralism in human moral judgment arises from the constructed nature of perceived harm. The article concludes by demonstrating how differing perceptions of harm contribute to political disagreements and how sharing stories of harm can help bridge moral divides.

This research is important for psychologists because it provides a deeper understanding of the cognitive and cultural underpinnings of morality. By understanding how perceptions of harm are constructed and how they vary across cultures and political ideologies, psychologists can gain insights into the roots of moral disagreements. This knowledge is crucial for addressing social issues, resolving conflicts, and fostering a more inclusive and harmonious society.

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.