The Quandary in Data Protection and Rights to Privacy of AI Technology Adoption in Malaysia
Abstract
Artificial Intelligence (AI) is increasingly taking hold throughout worldwide businesses. Since 2017, anticipated AI usage in Malaysia has increased by 32 percent due to innovative city projects and public safety and intelligent transportation applications. However, such AI development is afflicted by privacy and data breaches as the existing data protection regulation safeguards against unlawful commercial use of personal data. Recent developments reflect the failure of present legal mechanisms to address such infringements and effective data management and protection deficiencies. This study examines the legal concerns of privacy and data protection and problems associated with the use of AI in Malaysia. This research adopts a methodology of doctrinal research, a systematic method of legal reasoning, including analyzing primary and secondary resources. The findings imply that AI evolves, magnifying the ability to use personal information that may affect privacy. Thus, infringement of privacy and use of personal data without legal oversight or effective governance could result in privacy deprivation and abuse of personal data that might be used to perpetrate crimes
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Regulations are being implemented to employ stricter rules and enhance privacy.
“Since privacy is a much more serious issue in current times than before, regulations are being implemented to employ stricter rules and enhance privacy.”
From A Review of Trustworthy and Explainable Artificial Intelligence (XAI) (2023) · cites this paper as [22]
GDPR has already stated this issue and countries like Malaysia have also employed some regulations.
“GDPR has already stated this issue and countries like Malaysia have also employed some regulations [14], [22].”
From A Review of Trustworthy and Explainable Artificial Intelligence (XAI) (2023) · cites this paper as [22]
Cites
Artificial Intelligence: A Guide to Intelligent Systems
Negnevitsky, M. (2001) · eCite Digital Repository (University of Tasmania) · Cited by 2,207 · see citing works
Felten, E., Raj, M., & Seamans, R. (2021) · Strategic Management Journal · doi:10.1002/smj.3286 · Cited by 574 · see citing works
Wang, W., & Siau, K. (2019) · Journal of Database Management · doi:10.4018/jdm.2019010104 · Cited by 452 · see citing works
Machine Learning, Social Learning and the Governance of Self-Driving Cars
Stilgoe, J. (2017) · doi:10.2139/ssrn.2937316 · Cited by 376 · see citing works
Machine learning, social learning and the governance of self-driving cars
Stilgoe, J. (2018) · Social Studies of Science · doi:10.1177/0306312717741687 · Cited by 375 · see citing works
Artificial Intelligence: Structures and Strategies for Complex Problem Solving
Khorasani, E. S. (2008) · Scalable Computing Practice and Experience · doi:10.12694/scpe.v9i3.534 · Cited by 328 · see citing works
Kuo, R. J., Chen, C. H., & Hwang, Y.-C. (2001) · Fuzzy Sets and Systems · doi:10.1016/s0165-0114(98)00399-6 · Cited by 307 · see citing works
Towards a new generation of artificial intelligence in China
Wu, F., Lu, C., Zhu, M., Chen, H., Zhu, J., Yu, K., Li, L., Li, M., Chen, Q., Li, X., et al. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-020-0183-4 · Cited by 287 · see citing works
Governing Artificial Intelligence to benefit the UN Sustainable Development Goals
Truby, J. (2020) · Sustainable Development · doi:10.1002/sd.2048 · Cited by 266 · see citing works
Artificial intelligence for human flourishing – Beyond principles for machine learning
Stahl, B. C., Andreou, A., Brey, P., Hatzakis, T., Kirichenko, A., Macnish, K., Laulhé Shaelou, S., Patel, A., Ryan, M., & Wright, D. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2020.11.030 · Cited by 203 · see citing works
Artificial Intelligence: Risks to Privacy and DemocracyPreprint
Manheim, K. M., & Kaplan, L. (2018) · SSRN Electronic Journal · Cited by 180 · see citing works
Artificial intelligence and policy: quo vadis?
Lauterbach, A. (2019) · Digital Policy Regulation and Governance · doi:10.1108/dprg-09-2018-0054 · Cited by 114 · see citing works
The Economics of Artificial Intelligence: An Agenda
Agrawal, A. K., Gans, J. S., & Avi Goldfarb, B. (2019) · RePEc: Research Papers in Economics · doi:10.7208/chicago/9780226613475.001.0001 · Cited by 112 · see citing works
AI Ethics in Predictive Policing: From Models of Threat to an Ethics of Care
Asaro, P. (2019) · IEEE Technology and Society Magazine · doi:10.1109/mts.2019.2915154 · Cited by 110 · see citing works
Media and the Imaginary in History
Natale, S., & Balbi, G. (2014) · Media History · doi:10.1080/13688804.2014.898904 · Cited by 92 · see citing works
Ng, S. I., Ho, J. A., Lim, X. J., Chong, K. L., & Latiff, K. (2021) · Young Consumers · doi:10.1108/yc-06-2019-1006 · Cited by 92 · see citing works
Tygar, J. D. (2011) · IEEE Internet Computing · doi:10.1109/mic.2011.112 · Cited by 58 · see citing works
Artificial Intelligence and Deep Learning Applications for Automotive Manufacturing
Luckow, A., Kennedy, K., Ziolkowski, M., et al. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8622357 · Cited by 54 · see citing works
The AI advantage: how to put the artificial intelligence revolution to work
Vemuri, V. K. (2020) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2020.1756084 · Cited by 43 · see citing works
New perspectives on ethics and the laws of artificial intelligence
Magrani, E. (2019) · Internet Policy Review · doi:10.14763/2019.3.1420 · Cited by 35 · see citing works
Zhang, Y., Zhou, J., Xiang, Y., et al. (2017) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2017.2711040 · Cited by 33 · see citing works
Privacy in emergency circumstances: data protection and the COVID-19 pandemic
Ventrella, E. (2020) · ERA Forum · doi:10.1007/s12027-020-00629-3 · Cited by 32 · see citing works
Artificial Intelligence and the GDPR: Inevitable Nemeses?
Kesa, A., & Kerikmäe, T. (2020) · TalTech Journal of European Studies · doi:10.1515/bjes-2020-0022 · Cited by 28 · see citing works
Artificial intelligence classification methods of atrial fibrillation with implementation technology
Lim, H. W., Hau, Y. W., Lim, C. W., & Othman, M. A. (2016) · Computer Assisted Surgery · doi:10.1080/24699322.2016.1240303 · Cited by 21 · see citing works
The Legal and International Situation of AI, Robotics and Big Data With Attention to HealthcarePreprint
Puaschunder, J. M. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3472885 · Cited by 20 · see citing works
Group Privacy: The Right To Huddle
Bloustein, E. J. (2018) · Routledge eBooks · doi:10.4324/9781351319966-4 · Cited by 19 · see citing works
State of Data Privacy During COVID-19
Ahmad, N., & Chauhan, P. S. (2020) · Computer · doi:10.1109/mc.2020.3010549 · Cited by 17 · see citing works
Chassang, G., Thomsen, M., Rumeau, P., Sèdes, F., & Delfin-Rossaro, A. (2021) · AI Communications · doi:10.3233/aic-201523 · Cited by 17 · see citing works
Lee, Z. Y., Karim, M. E., & Ngui, K. (2021) · Information & Communications Technology Law · doi:10.1080/13600834.2021.1890678 · Cited by 12 · see citing works
Towards A Personal Data Protection Regime In Malaysia
Khaw, L. T. (2002) · Journal of Malaysian and Comparative Law · Cited by 11 · see citing works
REGULATING ARTIFICIAL INTELLIGENCE IN MALAYSIA: THE TWO-TIER APPROACH
Manap, N., & Abdullah, A. (2020) · UUM Journal of Legal Studies · doi:10.32890/uumjls.11.2.2020.8779 · Cited by 11 · see citing works
Schwab, D., Goulian, J., & Tchechmedjiev, A. (2013) · International Journal of Web Engineering and Technology · doi:10.1504/ijwet.2013.055713 · Cited by 9 · see citing works
ARTIFICIAL INTELLIGENCE – SCIENCE FICTION AND LEGAL REALITY
Koos, S. (2018) · Malaysian Journal of Syariah and Law · doi:10.33102/mjsl.v6i3.135 · Cited by 9 · see citing works
Artificial Intelligence and Big Data Analytics in Support of Cyber Defense
Leenen, L., & Meyer, T. A. (2020) · IGI Global eBooks · doi:10.4018/978-1-7998-7705-9.ch076 · Cited by 9 · see citing works
Selected issues regarding the Malaysian Personal Data Protection Act (PDPA) 2010
Ismail, N. (2012) · International Data Privacy Law · doi:10.1093/idpl/ips005 · Cited by 8 · see citing works
Artificial Intelligence in Health Policy – A Global Perspective
Moonesar, I. A., & Dass, R. (2021) · Global Journal of Computer Science and Technology · doi:10.34257/gjcsthvol21is1pg1 · Cited by 7 · see citing works
Personal Data Protection and Privacy Law in Malaysia
Cieh, E. L. Y. (2012) · Springer eBooks · doi:10.1007/978-3-642-33081-0_2 · Cited by 6 · see citing works
Rascão, J. P. (2020) · International Journal of Business Strategy and Automation · doi:10.4018/ijbsa.2020070101 · Cited by 6 · see citing works
Guarding privacy on the internet: privacy policy, government regulations and technology solutions
Bhasin, M. L. (2008) · International Journal of Internet Marketing and Advertising · doi:10.1504/ijima.2008.017023 · Cited by 5 · see citing works
Artificial Intelligence and the Privacy Paradox of Opportunity, Big Data and The Digital Universe
Smith, G. A. (2019) · International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) · doi:10.1109/iccike47802.2019.9004264 · Cited by 5 · see citing works
Balancing Open Justice and Privacy Rights in Adopting ICT in the Malaysian Courts
Mohamad, A. M., Hamin, Z., & Othman, M. B. (2017) · Advanced Science Letters · doi:10.1166/asl.2017.9629 · Cited by 4 · see citing works
Self-citationThe Scent Of A Woman: Governing The Gendered Crime Of Cyber Stalking
Rosli, W. R. W., & Hamin, Z. (2018) · The European Proceedings of Social & Behavioural Sciences · doi:10.15405/epsbs.2018.12.03.50 · Cited by 2 · see citing works
Self-citationVöneky, S. (2021) · Nomos Verlagsgesellschaft mbH & Co. KG eBooks · doi:10.5771/9783748925842-279 · Cited by 2 · see citing works
Standards for the artificial intelligence community
Blasch, E., & Sung, J. (2021) · doi:10.1117/12.2589025 · Cited by 1 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A Review of Trustworthy and Explainable Artificial Intelligence (XAI)
Chamola, V., Hassija, V., Sulthana, A. R., Ghosh, D., Dhingra, D., & Sikdar, B. (2023) · IEEE Access · doi:10.1109/access.2023.3294569 · Cited by 352 · see citing works
“GDPR has already stated this issue and countries like Malaysia have also employed some regulations [14], [22].”
Background
- Authors
- Kamaruddin, S., Wan Rosli, W. R., Mohd Saufi, N. N., Mohammad, A. M., & Hamin, Z.
- Affiliations
- Sultan Idris Education University (MY)
- Universiti Teknologi MARA,Faculty of Law,Selangor Darul Ehsan,Malaysia,40460
- Management & Science University,Faculty of Business Management & Professional Studies,Selangor Darul Ehsan,Malaysia,40460
- Universiti Utara Malaysia (MY)
- Universiti Teknologi MARA System (MY)
- ORCID
- Kamaruddin, Saslina
- Venue
- 2021 Innovations in Power and Advanced Computing Technologies (i-PACT)
- Publisher
- IEEE
- Published
- 2021-11-27
- Pages
- 1-5
- OpenAlex
- W4210994889
- Cited by
- 6
- References
- 44
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2
- FWCI
- 10.19
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Innovations in Power and Advanced Computing Technologies (i-PACT) (publishedVersion)
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Keywords
- artificial intelligence, data protection, right to privacy, personal data, data breaches, AI regulation, AI governance, Malaysia
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review