Misuse Of Data Research Articles

Exploring the Role of DNA Technology in Administration of Justice in India: A Comparative Analysis with USA

Introduction: There is an increasing prevalence of novel crimes employing advanced methods and technology which necessitates investigative agencies to employ meticulous and systematic approaches grounded in scientific nature to effectively address the situation. DNA fingerprinting is one such contemporary investigative technique which assumes a significant function within the field of forensic science. DNA Technology can be utilized to identify offenders with exceptional accuracy while absolving innocents. Objective: Despite the extensive use of DNA technology in administration of justice, there is no specific legislation for its use and regulation in India. This article aims to find out the significance of DNA technology in administration of justice in India and the challenges associated with it. It also tries to find gaps in the existing literature related to the use of DNA technology. Method: The research methodology adopted here is normative juridical which includes comprehensive analysis of legislative framework along with the Constitutional provisions. It has also referred to a variety of scholarly literature and landmark judicial decisions. Results: This article suggests that although DNA technology plays a significant role in the administration of justice, there are numerous challenges in relation to the use of DNA technology such as absence of a comprehensive law on the subject, privacy concerns of individuals, lack of well-equipped labs and shortage of staff, absence of database, misuse of sensitive data, mishandling of samples, etc. This all can be addressed by bringing a law and maintaining a database for which inspiration may be sought from countries like the USA. Conclusion: In the light of changing dynamics of criminal investigation and the sophistication adopted by criminals, it is necessary that agencies effectively utilize DNA technology for speedy justice. For regulating the use of such technology along with balancing the rights of individuals, India must enact a legislation at the earliest. It is necessary because the judicious use of DNA technology may change the face of the criminal justice system as it is capable of providing accurate evidence.

BEYOND LEGAL FRAMEWORKS AND SECURITY CONTROLS FOR ACCESSING CONFIDENTIAL SURVEY DATA IN THE UNITED STATES: ENGAGING DATA USERS IN DATA PROTECTION.

With growing demand for data reuse and open data within the scientific ecosystem, protecting the confidentialy of survey data and privacy of data subjects is increasingly important. Doing so requires more than legal procedures and technological controls; it requires social and behavioral intervention. In this research note, we delineate the disclosure risks of various types of survey data (e.g., longitudinal data, social network data, sensitive information, biomarkers, and geographic data), the current motivation for data reuse, and challenges to data protection. Despite rigorous efforts to protect data, there are still threats to protection of confidentiality in microdata. Unintentional data breaches, protocol violations, and data misuse are observed even in well-established restricted data access systems, indicating that the systems may all rely heavily on trust. Creating and maintaining that trust is critical to secure data access. We suggest four ways of building trust; User-Centered Design Practices; Promoting Trust for Protecting Confidential Data; General Training in Research Ethics; and Specific Training in Data Security Protocols, with an example of a new project 'Researcher Passport' by the Inter-university Consortium for Political and Social Research. Continuous user-focused improvements in restricted data access systems are necessary so that we promote a culture of trust among the research and data user community, train both in the general topic of responsible research and in the specific requirements of these systems, and offer systematic and holistic solutions.

Ethics and Law for the Use and Development of Artificial Intelligence Technology

The development and use of Artificial Intelligence is growing exponentially, resulting in various implications in multi-sectors such as misuse of personal data, assessments prone to bias, uncontrolled automation, etc.) There is a legal vacuum (absence of law) in the use of Artificial Intelligence, so ethical principles of use are needed as a basis for developing a legal framework for Artificial Intelligence in the form of international conventions (law making treaties). Ethics and Law for the Use and Development of Artificial Intelligence Technology is that the use of AI can be an alternative and new breakthrough as an effort to prevent and minimize violations of ethical codes such as by public auditors. In the audit process, AI is designed to collect and determine data dynamically and then process the data to detect fraud in a relatively shorter time and with a higher level of accuracy than auditors in general. However, in the audit process carried out by AI, if viewed from the law enforcement factor, it cannot be said to be a legal subject because the requirements for law enforcement factors, namely facilities and facilities, have not been fulfilled.

Security and Privacy Issues in Internet of Things (IoT) Devices Using COPRAS Method

This paper explores various security and privacy issues inherent in IoT devices, ranging from vulnerabilities in device firmware and software to data breaches and unauthorized access. We delve into the challenges of securing IoT devices due to their resource constraints, diverse communication protocols, and often lax security practices during development. Additionally, we discuss privacy implications stemming from the collection and sharing of sensitive personal data by IoT devices, as well as the potential for surveillance and data misuse. Furthermore, we examine the implications of IoT devices in critical infrastructure and industrial systems, where security breaches can have severe consequences. Finally, we propose potential solutions and best practices to address these challenges, including robust encryption methods, regular security updates, and improved authentication mechanisms, to ensure the security and privacy of IoT devices in an increasingly connected world. The exponential growth of IoT devices across various sectors such as smart homes, healthcare, transportation, and industrial automation underscores the importance of ensuring their security and privacy. As these devices become more integrated into daily life and critical infrastructure, any vulnerability can have widespread and severe consequences. The evaluation of alternative performances through Complex Proportionality Assessment (COPRAS) requires an understanding of key criteria, exploration of options, and comparison of relevant facts. Meeting the decision-makers' desire for comparing grades involves choosing among multiple options based on predetermined competing requirements. COPRAS offer a method for such assessments in real-world scenarios, where criteria are nuanced and values cannot be quantified numerically. From the result smart thermostat got the first rank whereas wearable fitness tracker is having the lowest rank.

Legal Protection of Patient's Electronic Medical Record: Indonesian Legal Perspective

Health is the most fundamental factor of every citizen, particularly in Indonesia. Considering that many people need health services, patients’ data are pivotal as they contain patients’ health and medical records, identity, examination, medication, and other services patients receive in health services. Medical record in Indonesia is regulated by the Minister of Health Regulation No. 269 of 2008 on Medical Record and the Minister of Health Regulation No .22 of 2022 on Electronic Medical Record. The transition to electronic medical records is expected to finish on 31 December 2023. Electronic Medical Records (EMRs), which are now being implemented across the healthcare system in Indonesia, have the potential to fulfill the rights of citizens in the healthcare sector. On the other hand, data security for patients requires protection, as electronic systems may be vulnerable to data breaches and misuse by unauthorized individuals. The objective of this research is to examine the legal protection for patients when their electronic medical record data is misused and to elucidate patients' rights in the realm of healthcare, particularly concerning medical records. The research employs a normative juridical approach with a legislative regulation focus. Article 29 of Minister of Health Regulation No. 22 of 2022 already addresses data protection for patients' personal information, although continuous monitoring of the implementation of patient's Electronic Medical Records is still necessary. The findings of this study emphasize the necessity of ensuring data protection guarantees for patients stored within electronic systems.

Application of Big Data Privacy Protection Based on Edge Computing in the Prediction of Martial Arts Training Movement Trajectory

With the development of science and technology, edge computing and big data privacy protection are more and more widely used in various fields. The application of big data privacy protection based on edge computing in the prediction of sport trajectories for martial arts training shows good performance and privacy protection. Edge computing can process and analyze data in real time to improve the accuracy and efficiency of sport trajectory prediction. Big data privacy protection can ensure the security of athletes' personal information and training data and prevent data leakage and misuse. However, existing related works still have some deficiencies in data processing speed, accuracy, and privacy protection. In this paper, the authors address these issues and propose an edge computing-based big data privacy protection method to improve the accuracy and security of sport trajectory prediction for martial arts training.

Analysis of Farm Data License Agreements: Do Data Agreements Adequately Reflect on Farm Data Practices and Farmers’ Data Rights?

Farm data license agreements are legal documents that play an important role in informing farmers about farm data processing practices such as collection, use, safeguarding, and sharing. These legal documents govern the exchange, access, and dissemination of farm data and are expected to provide legal protection against misuse of data. Despite their significant influence on farm data processing and governance, there is limited understanding of the content of farm data license agreements and standards for drafting them. Although online privacy policy content has been extensively studied, farm data agreements’ evaluation and analysis have been overlooked. This study aims to investigate the structure, content, and transparency of farm data licenses. We collected 141 agricultural terms of use agreements and used natural language processing methods such as keyword and keyphrase analysis to perform text feature analysis, Flesch Readability Ease Score and Flesch Grade Level readability analysis, transparency analysis, and content analysis to gain insight into common data practices adopted by the agriculture technology providers. We also manually reviewed these agreements to validate the results and strengthen the observations. The findings show that data agreements are long, complex, and difficult to read and comprehend. The results suggest that 95% of the agreements fall under the difficult-to-read category and close to 75% of the policies require university-level education to understand the content. Furthermore, it is noted that some of the data management practices are not given adequate attention and are not as frequently mentioned in the agreements as expected. Finally, our analysis enabled us to provide recommendations on the content of farm data license agreements and strategies to improve them.

Perceptions of Nigerian medical students regarding their preparedness for precision medicine: a cross-sectional survey in Lagos, Nigeria

BackgroundAdvances in precision medicine in Nigeria suggest improving genomics education and competency among healthcare practitioners to facilitate clinical translation. Due to the scarcity of research in this area, this study aimed to assess Nigerian medical students’ perceptions about their preparedness to integrate precision medicine into their future clinical practice.MethodsThis was an institution-based cross-sectional study of medicine and surgery students in their clinical years attending the two fully accredited colleges of medicine in Lagos, Nigeria, between April and October 2022 using an adapted tool administered via Google Forms. The survey assessed their awareness, perceptions about knowledge, ability, and attitudes toward precision medicine, ethical concerns, and perceptions about their education in precision medicine. Multivariate linear regression models were used to assess factors associated with students’ perceptions of their knowledge, ability, and attitudes.ResultsA total of 300 students completed the questionnaires with a response rate of 40%. Awareness of genomic medicine terminology was high (92.0%). Responses to knowledge and ability questions revealed notable gaps, however, respondents had positive attitude scores overall. Higher medical school year was independently associated with lower knowledge (ptrend = 0.003) and ability (ptrend = 0.005) scores, and knowledge score was independently associated with a higher ability score (β: 0.76 95%CI: 0.67, 0.84; p < 0.001). Attitude scores significantly increased with increasing medical school year (ptrend = 0.04). The respondents mostly indicated concerns about government and corporate bodies’ misuse of genomic data (35.7%) and the widening of socioeconomic disparities (34.0%). Although 65.0% of the respondents thought it important to learn about precision medicine, only 11.3% felt that their education had adequately prepared them for precision medicine, knew who to ask questions regarding genomic testing (10.7%), and felt their professors had encouraged the use of precision medicine (10.3%).ConclusionDespite high awareness of precision medicine terminology and overall positive attitudes, our findings highlight gaps in knowledge and ability to integrate genomics into the care of patients and a need to improve precision medicine education among Nigerian medical students.

Analisis Hukum Penyalahgunaan Data Pribadi pada Layanan Keuangan Fintech Lending

Misuse and leakage of personal data has become a concern in Indonesian society today. Facts show that in 2022 Indonesia has been ranked number 3 with the most cases of personal data leakage in the world. A total of 12.74 million personal data has been leaked in the implementation of fintech lending services in Indonesia. This research aims to provide an explanation of the legal analysis resulting from leaks of personal data and misuse of personal data in the implementation of fintech lending services in Indonesia. The results of the analysis from research data processing are that this personal data has been regulated in Law Number 27 of 2022 concerning Personal Data Protection which was ratified in 2022 to be precise on October 17 by the President of the Republic of Indonesia as an Urgency Law. Law Number 27 of 2022 clearly contains legal protection efforts for the importance of personal data, sanctions and also legal protection provided which aims to prevent misuse of personal data.&#x0D;

Federated Learning- Hope and Scope

People are suffering from” data obesity” as a result of the expansion and quick development of various Artificial Intelligence (AI) technologies and machine learning fields. The management of the current techniques is becoming more challenging due to the data created in the Smart-Health and Fintech service sectors. To provide stable and reliable methods for processing the data, several Machine Learning (ML) techniques were applied. Due to privacy-related issues with the aforementioned two providers, ML cannot fully use the data, which becomes difficult since it might not give the results that were expected. When the misuse and exploitation of personal data were gaining attention on a global scale and traditional machine learning (CML) was facing difficulties, Google introduced the concept of Federated Learning (FL). In order to enable the cooperative training of machine learning models among several organizations under privacy requirements, federated learning has been a popular research area. The expectation and potential of federated learning in terms of smart-health and fintech services are the main topics of this research.

Views on sharing mental health data for research purposes: qualitative analysis of interviews with people with mental illness

BackgroundImproving the ways in which routinely-collected mental health data are shared could facilitate substantial advances in research and treatment. However, this process should only be undertaken in partnership with those who provide such data. Despite relatively widespread investigation of public perspectives on health data sharing more generally, there is a lack of research on the views of people with mental illness.MethodsTwelve people with lived experience of mental illness took part in semi-structured interviews via online video software. Participants had experience of a broad range of mental health conditions including anxiety, depression, schizophrenia, eating disorders and addiction. Interview questions sought to establish how participants felt about the use of routinely-collected health data for research purposes, covering different types of health data, what health data should be used for, and any concerns around its use.ResultsThematic analysis identified four overarching themes: benefits of sharing mental health data, concerns about sharing mental health data, safeguards, and data types. Participants were clear that health data sharing should facilitate improved scientific knowledge and better treatments for mental illness. There were concerns that data misuse could become another way in which individuals and society discriminate against people with mental illness, for example through insurance premiums or employment decisions. Despite this there was a generally positive attitude to sharing mental health data as long as appropriate safeguards were in place.ConclusionsThere was notable strength of feeling across participants that more should be done to reduce the suffering caused by mental illness, and that this could be partly facilitated by well-managed sharing of health data. The mental health research community could build on this generally positive attitude to mental health data sharing by following rigorous best practice tailored to the specific concerns of people with mental illness.

Ethical Leadership in Information Technology Decision Making and its Impact on Risk Management

In the rapidly growing digital era, information technology has become an integral part of almost all aspects of our lives, including in the world of business and management. Appropriate and effective use of information technology is the key to achieving competitive advantage in today's competitive business environment. However, making decisions related to information technology is not an easy task, as information technology is often complex and high-risk. The purpose of this study is to analyse ethical leadership in information technology-related decision making and its impact on risk management. The method used is a qualitative literature review that focuses on an in-depth understanding of the topic in the time span from 2006 to 2023. The main objective of this method is to identify, analyse, and synthesise relevant scientific literature that has been published in various journals, conference papers, and other academic sources accessible through Google Scholar. The study results show that ethical leadership plays a central role in ensuring that IT-related decisions are taken with ethical principles in mind and with the aim of minimising risk. Ethical leadership contributes to the avoidance of data misuse, creating a culture of transparency and accountability, ensuring fair use of technology, and being mindful of the impact of IT decisions on society and the environment.

Technological paradoxes and artificial intelligence implementation in healthcare. An application of paradox theory

AI is transforming healthcare system with many innovations in diagnosis, drug research and advancement in medical treatments. But there are several concerns and dilemmas related to data misuse, AI efficiency for critical diagnostic services, users' resistance, investment costs, funding issues, and so on that have been raised by many previous studies on the effective integration of AI in clinical settings. Using paradox theory in the organisational settings, the present study discusses several technological paradoxes associated with the adoption of AI in healthcare. In this regard, the study examines the views of diverse medical practitioners about using AI services for several medical needs. The study analyses the efficacy and limitations of AI services which develop several ethical dilemmas in the mind of medical practitioners and also suggest a few strategies for the adoption. Using grounded theory approach, the study collected views of 62 medical practitioners on these dimensions. The primary drivers to the adoption identified in the present study are: ease of use, automation efficacy, diagnostic accuracy, and cost efficiency. A lack of training and education, cultural and religious considerations, privacy issues and work insecurity are some of the concerns highlighted by the medical staffs. The study inferred a few paradoxes or ethical dilemmas of practitioners which need attentions. The study contributes to the existing literature on paradox theory and AI, and identifies a few under-discussed areas, drivers, and barriers of AI services are highlighted in the paper, which may lead to ethical concerns and steer AI adoption in healthcare.

British South Asian ancestry participants views of pharmacogenomics clinical implementation and research: a thematic analysis

BackgroundSouth Asian ancestry populations are underrepresented in genomic studies and therapeutics trials. British South Asians suffer from multi-morbidity leading to polypharmacy. Our objective was to elucidate British South Asian ancestry community perspectives on pharmacogenomic implementation and sharing pharmacogenomic clinical data for research.MethodsFour focus groups were conducted (9–12 participants in each). Two groups were mixed gender, while one group was male only and one was female only. Simultaneous interpretation was available to participants in Urdu and Bengali. Focus groups were recorded and abridged transcription and thematic analysis were undertaken.ResultsThere were 42 participants, 64% female. 26% were born in the UK or Europe. 52% were born in Bangladesh and 17% in Pakistan. 36% reported university level education.Implementation of pharmacogenomics was perceived to be beneficial to individuals but pose a risk of overburdening resource limited systems. Pharmacogenomic research was perceived to be beneficial to the community, with concerns about data privacy and misuse. Data sharing was desirable if the researchers did not have a financial stake, and benefits would be shared.Trust was the key condition for the acceptability of both clinical implementation and research. Trust was linked with medication compliance. Education, outreach, and communication facilitate trust.Conclusions (Significance and Impact of the Study)Pharmacogenomics implementation with appropriate education and communication has the potential to enhance trust and contribute to increased medication compliance. Trust drives data sharing, which would enable enhanced representation in research. Representation in scientific evidence base could cyclically enhance trust and compliance.

Perlindungan Hukum Terhadap Data Pribadi Masyarakat Dalam Pendaftaran Dan Verifikasi Partai Politik Sebagai Peserta Pemilihan Umum

The requirements for political parties to participate in the general elections in Indonesia include passing the registration and verification stages by the General Election Commission through a platform called the Political Party Information System (Sipol). The verification process consists of administrative and factual verification, which includes research and matching of the requirements as a participant in the general election, one of which is membership in a political party. However, this membership has caused problems due to the rampant acquisition of memberships through the use of the Population Identification Number (NIK). This research aims to assert that personal data must be protected with simultaneous protection as a maximal effort to eliminate the misuse of personal data by political parties. The research method used is normative juridical by using secondary data sources and supported by primary laws, as well as a qualitative descriptive method to collect data through interviews. The results of this research show that the protection of personal data against the misuse of public names is crucial. Thus, laws that regulate the general protection of personal data can be a reference in legal protection efforts in such cases. Moreover, on October 17, 2022, the President of Indonesia has enacted Law No. 27 of 2022 concerning Personal Data Protection, which specifically (lex specialis) regulates the protection of personal data

Metaverse Applications in Medical Education

Learning and teaching through personal computers have come a long way (1). Over the past two decades, Friedman has described the concept of the "amazing medical education machine" and how medical education can grow incrementally in space, time, and content through the appropriate use of this technology. With the advent of the Metaverse, this amazing medical learning machine has now become a reality. The Metaverse is a combination of "meta" and "universe" that describes a virtual environment connected to the physical world (2). In educational concepts, Metaverse is a term used to describe a variety of pervasive technologies, including virtual reality, augmented reality, or mixed reality, which are used to advance education and learning practices (3). The use of Metaverse in medical education offers new technological and educational capabilities in improving the abilities of health care professionals in patient care, medical knowledge, teamwork, diagnostic reasoning and critical thinking (4, 3). For trainees, with the help of Metaverse, a headset device was used to place them in the space and conditions similar to their working environments, similar to inside the room and next to the patient's bed. This new format allows teams of learners to interact with patients, peers, and educators while simultaneously visualizing the patient's clinical findings, imaging, and laboratory studies at the bedside (2). In another study, the research team developed a multitasking virtual reality application for cardiac arrest resuscitation. This program allows four interns to be in a "virtual room" and collaborate to care for a cardiac arrest patient. In short, medical education has also grown and developed according to new technologies. We need to know how to best use these unique features of the Metaverse in learning design and the overall future of medical education and therapy (1, 5). Metaverse can be used to simulate real-world scenarios, provide interactive feedback and personalized learning based on the needs and preferences of individual learners. This tool can be used to simulate real environments such as hospitals, operating rooms or natural environments, which can help medical students develop their skills and knowledge in a safe and controlled environment To develop (3,4). Research results show that learning based on clinical scenarios simulate real life and continuously improve learning results. Metaverse can improve experiential learning through the integration of effective educational approaches, such as problem-based learning, game-based learning, and scenario-based learning (6). The development of virtual reality simulation technologies in health care systems can be used not only in surgeries, but also in diagnosis, rehabilitation and education. The experiences of using Metaverse should be expanded so that health care providers and professors can understand the necessity of using it (5, 7). He pointed out the limitations of the Metaverse, weaker social connections and the possibility of violating one's privacy. In addition, committing various crimes in cyber space may happen due to the anonymity of people. The following suggestions can be used for educational use of Metaverse: professors should carefully analyze how students understand Metavers. also, educational Metaverse platforms should be created to prevent misuse of students' data (8).

Building public trust and confidence in secondary use of health data in Ireland

Abstract Background Secondary use of health data can drive research and healthcare improvements with implications for policy and practice. However, relevant legislation, implementation of technical safeguards, and ethical data management are essential. Existing evidence suggests general public support for secondary data use, but with specific concerns about privacy, confidentiality, misuse of data and trust. The aim of this study is to explore key stakeholders’ perspectives on secondary health data use in Ireland, and mechanisms to build a culture of trust. Methods The study adopts a qualitative cross-sectional approach. Participants include academics and researchers, healthcare professionals, data controllers and ethics experts, industry, and patients and public, recruited through purposive sampling. Data is collected through focus groups discussions, and reflexive thematic analysis is employed. Results The preliminary results suggest that benefits of secondary data use include access to large datasets, streamlined research, reduced bias, and cost-effectiveness, which may lead to improved patient outcomes. Barriers include an underdeveloped national data infrastructure, difficulties with access and linkage, complex ethical regulation, and narrow predetermined indices of health. Concerns related to data sharing are context-dependent, and influenced by patients’ socio-demographic characteristics. Trust appears to be both a bottom-up and top-down process, facilitated through clear communication, organizational openness, transparency, accountability, fairness, respect, and patient and public involvement (PPI). Conclusions The study identifies strong support for secondary health data use among the stakeholders, notwithstanding an identified need for structural improvements, strong safeguards, education and training, and meaningful PPI. This research helps inform public health practice and policies towards building a culture of trust pertaining to secondary data use. Key messages • This study produces novel insights to help advance research and policy on the barriers and facilitators to building trust and confidence in the access and use of health data for secondary purposes. • This study contributes to qualitative research methods related to eliciting people's views and perspectives in a safe, collaborative and efficient manner.

Hospital Legal Responsibilities for Misuse of Patient Personal Data In Electronic Medical Records

The purpose of this study was to analyze the patient's personal data protection law in the electronic medical record and to analyze the legal responsibility of the hospital for the misuse of patient's personal data in the electronic medical record. This research uses normative research methods and uses statutory and conceptual approaches. The issuance of Regulation of the Minister of Health Number 24 of 2022 concerning Medical Records which requires hospitals to maintain electronic medical records no later than December 31, 2022. The transition from conventional medical records to electronic medical records carries the risk of misusing patient personal data. The results of this study conclude that hospitals as personal data controllers and electronic system operators are required to implement Law Number 27 of 2022 concerning Protection of Personal Data in organizing electronic medical records except those specifically regulated by other laws and regulations and hospitals as corporations have legal responsibilities for misuse of patient personal data in electronic medical records, namely administrative liability, civil liability and criminal liability. &#x0D;

The algorithm and model of user data privacy protection psychological anxiety

BackgroundWith the development of smart elderly care technology, the collection and use of user data caused privacy concerns and psychological anxiety. By studying algorithms and models that protect the privacy of user data, it is possible to prevent unauthorized access and misuse of data and promote the sustainable development of technology.Objects and MethodsSPSS23.0 was used to conduct a quantitative investigation and research, and the sample included 200 users using smart elderly care technology. The Stanford Privacy Concerns Questionnaire (PCQ) was used to assess the level of privacy anxiety among users. Algorithms and models, such as data encryption and blockchain technology, are used to discuss the privacy protection of user data.ResultsThe results showed that users had high psychological anxiety about data privacy protection in smart elderly care technology. According to the data, 70% of users expressed concerns about data breaches and privacy violations. However, after the analysis and application of the model and algorithm, the psychological anxiety of users on data privacy protection has been significantly reduced, and 50% of users are satisfied with the privacy protection measures taken.ConclusionsIn the context of smart elderly care, users’ psychological anxiety about data privacy protection exists. The introduction of new algorithms and models, such as data encryption and blockchain technology, can effectively reduce the psychological anxiety of users and improve the acceptance of data privacy protection measures.AcknowledgementThe Shaanxi Provincial Education Science 13th Five Year Plan (2020) project, No.SGH20Y1428.

Disclosure Standards for Social Media and Generative Artificial Intelligence Research: Toward Transparency and Replicability.

Social media dominate today's information ecosystem and provide valuable information for social research. Market researchers, social scientists, policymakers, government entities, public health researchers, and practitioners recognize the potential for social data to inspire innovation, support products and services, characterize public opinion, and guide decisions. The appeal of mining these rich datasets is clear. However, there is potential risk of data misuse, underscoring an equally huge and fundamental flaw in the research: there are no procedural standards and little transparency. Transparency across the processes of collecting and analyzing social media data is often limited due to proprietary algorithms. Spurious findings and biases introduced by artificial intelligence (AI) demonstrate the challenges this lack of transparency poses for research. Social media research remains a virtual "wild west," with no clear standards for reporting regarding data retrieval, preprocessing steps, analytic methods, or interpretation. Use of emerging generative AI technologies to augment social media analytics can undermine validity and replicability of findings, potentially turning this research into a "black box" enterprise. Clear guidance for social media analyses and reporting is needed to assure the quality of the resulting research. In this article, we propose criteria for evaluating the quality of studies using social media data, grounded in established scientific practice. We offer clear documentation guidelines to ensure that social data are used properly and transparently in research and applications. A checklist of disclosure elements to meet minimal reporting standards is proposed. These criteria will make it possible for scholars and practitioners to assess the quality, credibility, and comparability of research findings using digital data.