An investigator’s relationship to an organization affects, or gives the appearance of affecting, his or her objectivity in the conduct of scholarly or scientific research, a conflict of interest is said to occur. The relationship does not have to be personal or financial. Most guidelines require authors to disclose such conflicts when submitting a manuscript.

A conflict of interest occurs when an individual's or organization's competing interests—financial, personal, or professional—could potentially influence their motivations or actions in their roles within the publication process.

A conflict of interest, also known as a competing interest, can occur when an Author, Editor, peer reviewer or their employer or sponsor, have a financial, commercial, legal or professional relationship with other organizations, or the people working with them, that could influence the research. Each journal article must carry a Conflict of Interest statement, whether there is a potential conflict or not. Authors and peer reviewers must disclose any financial relationships that could influence their work. This includes, for example, consultancies, employment, stock ownership, patents or promised benefits as an outcome of the work. Authors and peer reviewers should also disclose any personal relationships, academic collaborations or other non-financial associations that might present a potential conflict of interest.

A conflict of interest arises whenever there is any potential bias that could affect a researcher's work. Conflicts of interest can include both financial and non-financial gains. Almost all scientific and non-technical journals require authors to disclose potential or actual conflicts of interest related to their study.

Authors who use AI tools in the writing of a manuscript, production of images or graphical elements of the paper, or in the collection and analysis of data, must be transparent in disclosing in the Materials and Methods (or similar section) of the paper how the AI tool was used and which tool was used. Authors are fully responsible for the content of their manuscript, even those parts produced by an AI tool, and are thus liable for any breach of publication ethics. At submission, all authors must identify potential conflicts of interest in the electronic Copyright Transfer Agreement and within the article submitted for publication. Authors should err on the side of full disclosure and provide as much information as possible.

COPE joins organisations, such as WAME and the JAMA Network among others, to state that AI tools cannot be listed as an author of a paper. AI tools cannot meet the requirements for authorship as they cannot take responsibility for the submitted work. As non-legal entities, they cannot assert the presence or absence of conflicts of interest nor manage copyright and license agreements. Authors who use AI tools in the writing of a manuscript, production of images or graphical elements of the paper, or in the collection and analysis of data, must be transparent in disclosing in the Materials and Methods (or similar section) of the paper how the AI tool was used and which tool was used. Authors are fully responsible for the content of their manuscript, even those parts produced by an AI tool, and are thus liable for any breach of publication ethics.

The Securities and Exchange Commission is proposing new rules governing conflicts of interest associated with the use of predictive data analytics and certain other technologies. The proposed rules are intended to prevent firms from using certain technologies, including artificial intelligence, to place the firm’s interests ahead of investors’ interests. A conflict of interest is defined broadly and includes any situation where a covered technology considers any firm-favorable information in an investor interaction, even if the firm does not ultimately place its interests ahead of investors’ interests.

In the world of academic and scientific research, the integrity and transparency of research work are of paramount importance. One significant threat to this integrity is the presence of conflict of interest (COI), where personal or financial relationships might influence, or appear to influence, the research outcomes.

Ethical publication practices will require transparency about how AI was used in writing, data analysis, or interpretation to avoid misleading readers and maintaining the integrity of the research process. Authors and journals will need clear guidelines about disclosing the use of AI in the research process. AI tools could assist journal editors and editorial staff in monitoring compliance with publication ethics, such as adherence to the Committee on Publication Ethics (COPE) guidelines. AI could automatically identify instances where ethical standards are at risk or where conflicts of interest may not have been disclosed.

Fact-checking has become a key response to disinformation during crises and conflicts, but its role is increasingly contested due to concerns about its effectiveness and its co-optation by different political actors. In polarized, high-choice environments, fact-checking is often embedded within partisan and state-aligned infrastructures, shaping validation and rejection of knowledge claims. Whereas crowdsourcing models rely on distributed judgment and visible contestation, AI-driven fact-checking concentrates epistemic power, the power to define what counts as credible or false, within opaque systems whose outputs are often treated as neutral or authoritative.

Software named the Artificial Intelligence Review Assistant, or AIRA, checks for potential conflicts of interest by flagging whether the authors of a manuscript have financial ties to corporations or other organizations that may have influenced their work. AIRA compares the names of manuscript authors to databases of clinical trials and patents to identify possibly relevant relationships. Journal editors then review the flagged items to decide whether they constitute a conflict of interest or should be disclosed.

The purpose of this policy is to set forth acceptable parameters relating to possible conflicts of interest which may arise from outside professional activities and sponsored research. Activities that constitute a conflict of interest where there is significant financial interest are prohibited unless a plan to reduce, eliminate or manage the conflict has been expressly approved; activities that constitute a conflict of interest where there is a substantial interest are unlawful. Any person involved in the design, conduct, or reporting of research must disclose any potential or actual significant or substantial financial interests that may appear to affect the design, conduct or reporting of such research, and management plans can include public disclosure, independent monitoring of research, modification of the research plan, or disqualification from participation in affected portions of the research.

Honesty in developing, carrying out, reviewing, reporting and communicating on research transparently, fairly, thoroughly and impartially. This principle includes disclosing that generative AI has been used. Accountability for the research from idea to publication, for its management and organisation, for training, supervision and mentoring, and for its wider societal impacts. This includes responsibility for all output that a researcher produces, underpinned by the notion of human agency and oversight. Researchers are accountable for the integrity of the content they produce generated by or with the support of AI tools.

At submission, authors should declare any intellectual property relating to the code and themselves in a conflict of interest statement. Obfuscation or non-disclosure of known COIs of editors, reviewers or authors. Recommending reviewers with conflicts of interest known to the author without disclosing these conflicts. Providing a false, fabricated, or knowingly inaccurate affiliation, including listing a former or unaffiliated institution for the purposes of prestige or misrepresentation of where the work was conducted, may constitute a breach of publishing ethics and could lead to an investigation involving the relevant institution(s).

The paradox of AI-based technology in fact-checking lies in its dual nature as both a tool to help verify facts and a tool to create or amplify information disorder. Generative AI technologies, large language models (LLMs) in particular, have the potential to assist fact-checkers at various stages of their work, but while AI can significantly aid the detection and mitigation of misinformation, risk mitigation strategies are required to ensure its responsible use. Research shows that human expertise is still essential for AI fact-checking because AI systems cannot fully grasp context, intent or credibility, and one challenge is encoding complex concepts such as ethics and critical thinking into algorithms.

This article examines the obstacles to the effectiveness of fact-checking, focusing primarily on the pervasive impact of entrenched biases. In the declaration of competing interest, the authors list related works on AI agency in fact-checking and source type in health misinformation fact-checking, indicating transparency about their research activities in adjacent topics. The declaration of competing interest section is used to disclose relationships or activities that could potentially be perceived as influencing the research, underscoring the importance of managing and declaring conflicts of interest in studies about fact-checking and AI.

A conflict of interest takes place when there is any interference with the objective decision making by an editor or objective peer review by the referee. Such secondary interests could be financial, personal, or in relation to any organization.

Using artificial intelligence (AI) in research offers many important benefits for science and society but also creates novel and complex ethical issues. The code stipulates that researchers should report “their results and methods including the use of external services or AI and automated tools” and considers “hiding the use of AI or automated tools in the creation of content or drafting of publications” as a violation of research integrity. Recommendations for ethical use of AI in research include that researchers should disclose, describe, and explain their use of AI in research, including its limitations, in language that can be understood by non-experts.

The SEC's proposed conflict of interest rules are intended to prevent broker-dealers and investment advisers from using AI and other "covered technologies" in ways that place the firm's interests ahead of investors' interests. Firms would be required to evaluate any use or reasonably foreseeable potential use of covered technology, identify any conflicts of interest related to that use, and eliminate or neutralize those conflicts’ effects. The rules also require written documentation of determinations as to whether there was a conflict of interest and how the effect of any conflict has been eliminated or neutralized, as well as written policies and procedures designed to achieve compliance with the proposed conflicts rule.

As a publisher, we have a moral obligation to preserve trust in our processes and publications for our authors, customers, and readers. Any use of AI tools and AI-assisted technologies must be transparently disclosed in manuscripts to maintain research publishing ethics and integrity. We expect authors to follow the guidance of the Committee on Publication Ethics (COPE) and other relevant bodies on issues such as authorship, conflicts of interest, and research integrity.

The core problem hasn’t changed: a conflict of interest arises when personal incentives corrupt professional judgment. Models trained on past behaviors can hardwire yesterday’s conflicts into tomorrow’s decisions. The veneer of objectivity gives cover to deeply subjective inputs; just because it looks like math doesn’t mean it’s clean. Conflicts of interest haven’t vanished; they’ve become faster, smarter, and harder to catch.

A growing body of interdisciplinary research and case evidence provides a comprehensive review of emerging AI-driven disinformation techniques and corresponding policy recommendations for democratic resilience. The authors recommend fostering agile, pre-competitive collaboration among public, private, and academic stakeholders to accelerate the development of adaptive defenses against AI-enabled disinformation. Governments, platforms, and international bodies should jointly fund interdisciplinary R&D initiatives at the intersection of AI, cybersecurity, behavioral science, and information integrity, including building shared threat modeling environments where researchers can test adversarial AI tactics and co-develop countermeasures.

The risks posed by future Frontier AI will include the risks we see today, but with potential for larger impact and scale. Artificial intelligence, both at the Frontier and more broadly, poses both risks and opportunities today. These include enhancing mass mis- or disinformation and deepfakes, enabling cyber-attacks, reducing barriers to access harmful information and enabling fraud. Lack of safety, controllability, and misuse cause these systems to fail in unexpected ways.

The Oversight Board reiterates that Meta should ensure that fact-checkers are adequately resourced and have guidance on prioritizing content from different sources, including AI-generated content. It recommends that Meta create a separate Community Standard for AI-generated content and invest in stronger detection tools for AI-generated multi-format content. The Board stresses that fact-checking operations need clear policies, labeling protocols, and escalation channels for AI tools, as well as in-house expertise and action, including labeling and investigating posting accounts and pages, to manage risks posed by AI during conflicts and crises.

Building on this multidisciplinary approach, this report derives policy principles that can inform how California approaches the use, assessment and governance of frontier AI. A well-designed disclosure and verification regime offers significant benefits not only to the public but also to foundation model developers, by establishing industry-wide transparency standards and third-party verification mechanisms. Companies can demonstrate compliance with best practices through transparency reporting and external audits, which help manage conflicts of interest and maintain trust in oversight processes.

This paper aims to propose guidelines for AI research ethics in scientific research for publications. These guidelines can inform publishers, editors, reviewers, and authors about the ethical use of generative AI in scientific writing and data analysis. Conflict of Interest: No potential conflict of interest relevant to this article was reported. The authors declare that there is no conflict of interest regarding the publication of this paper.

A conflict of interest occurs when a researcher's personal, financial, or professional relationships could compromise, or even just appear to compromise, their objectivity in conducting or reporting research.

Using AI ethically ensures that advocacy is grounded in truth and transparency. The PRSA guidelines emphasize honesty, expertise, independence, loyalty, and fairness in AI-assisted work, including the need to fact-check AI-generated content to prevent the spread of misinformation and ensure all communication remains truthful and accurate. Practitioners are advised not to use AI in ways that betray trust, misrepresent intentions, or conceal conflicts, and to ensure that disclosure of AI use and potential conflicts is consistent with applicable laws, regulations, or best practices in their jurisdiction.

Check whether key stakeholders in your field of study, the publisher or sponsor discuss the integration of AI generated text, data and images with proposals. Many publishers and sponsors now require disclosure of AI use and potential conflicts of interest related to funding, affiliations, or commercial benefits that could influence the research. Researchers should consult the Committee on Publication Ethics (COPE) and similar bodies for standards on integrity and AI.

This memorandum discusses a number of existing authorities in order of their likely utility for AI oversight, including options to address antitrust concerns. One option for addressing such antitrust concerns would be the use of Section 708 of the Defense Production Act to officially sanction voluntary agreements between companies that might otherwise violate antitrust laws. The analysis highlights the need for regulatory structures and oversight mechanisms for frontier AI models, including issues of competition, transparency, and accountability among companies that develop or audit these models.

The FTC’s proposed policy statement on AI accuracy and ideological manipulation of AI outputs notes that AI companies can avoid Section 5 liability by making clear, conspicuous, and adequate disclosures that their outputs may be inaccurate or ideologically biased. The statement highlights concerns that AI outputs could be optimized in ways that reflect undisclosed commercial or ideological interests, creating potential conflicts between the AI provider’s incentives and users’ expectations of accurate, neutral information. Transparency about how AI systems are trained, optimized, and monetized is presented as a key mechanism for managing these conflicts and maintaining trust.

Is AI transforming the challenges faced by fact-checking organisations? Is it turbo-charging misinformation on digital platforms or are fact-checkers managing to harness it? The discussion in this video explores how AI tools are being integrated into fact-checking workflows, the ethical challenges that arise, and concerns about transparency and accountability when automated systems are used to judge factual claims.

Conflicts of interest fundamentally undermine the principles of fair dealing, objective decision-making, and fiduciary responsibility that form the foundation of trust in both public and private institutions. Publication analysis identifies potential conflicts where authors fail to disclose relevant financial relationships or institutional affiliations.

Major journals and publishers generally treat employment by a company whose products or services are discussed in a paper as a potential conflict of interest that must be disclosed, rather than as a prohibition on publication. Typical policies define conflicts of interest as financial relationships (such as salary, consulting fees, stock ownership, or patents) or other professional ties that could reasonably be perceived to influence the work, and require disclosure in a conflict of interest statement. Whether the situation is considered a conflict depends on the specific relationship, its magnitude, and the journal’s policies.

Having a relationship or interest — whether financial, professional, personal, political, or something else — related to your research can create a conflict of interest. It is important to identify when a conflict might exist so it can be managed to protect research integrity.