By Muhammad Syawalfiza
Introduction
Imagine asking an AI assistant a simple question: “Where and when do I vote?”
The answer looks clear and confident. Unfortunately, the polling date is wrong.
The mistake might arise because the system uses outdated information, retrieves the wrong record, misunderstands a source or generates an answer that the source does not support. The problem may become more serious if the answer is repeated by news outlets, social-media accounts or other AI systems.
Who should be responsible? The Election Commission, which maintains the official information? The company that developed the AI model? The organisation that incorporated the model into its service? Or the platform through which the answer reaches voters?
The answer depends on what went wrong, what each organisation could reasonably control and what the applicable law requires.
My earlier article, From Official Election Data to AI-Generated Answers: Responsibility Across the Voter-Information Chain, explored how incorrect AI-generated election information might be traced and corrected. This companion examines a related question: how should Malaysia's legal and regulatory institutions support that process?
The issue has become more pertinent following Japan's latest legislative and policy developments concerning election misinformation. Japan is proposing measures to improve the visibility of trustworthy information, label certain AI-generated material, address financial incentives for misinformation and strengthen platform responses. Some of these objectives overlap with my earlier proposal, although the mechanisms differ.
This article examines the similarities and differences, drawing on selected experience from Japan, Singapore, South Korea and ASEAN. Its purpose is not to claim that Malaysia needs an entirely new regulatory model or that the proposed approach is unprecedented. Instead, it considers how established accountability principles might be applied more precisely to election information in Malaysia.
1. Malaysia's regulatory position: an evolving framework
Malaysia is not without rules relevant to AI-generated election information. Its existing legal framework includes the Communications and Multimedia Act 1998 (CMA), the Online Safety Act 2025 (ONSA), the Personal Data Protection Act 2010 (PDPA), the Cyber Security Act 2024 and election-related legislation. These instruments have different legal statuses, scopes and functions. Some impose binding statutory duties or create offences; others provide institutional powers or regulatory mechanisms. They should not be treated as interchangeable, and none should be assumed to create a general law of AI-output accuracy merely because it may be relevant to an AI service [4–8].
1.1 Online safety and communications law
ONSA took effect on 1 January 2026. It is binding legislation that establishes duties for specified licensed service providers and provides mechanisms for addressing legally defined harmful content, reporting concerns and regulatory enforcement [6].
An important distinction must be maintained: an incorrect AI-generated polling date does not automatically constitute harmful content under ONSA or a criminal offence under the CMA. The relevant statutory definitions, legal elements and facts must be examined. Draft guidance, policy proposals or comparative approaches cannot expand those statutory provisions unless adopted through a legally valid instrument.
Consider three situations.
An AI assistant accidentally gives the wrong polling date. A political operator deliberately uses an AI system to distribute false voting instructions. A platform receives credible reports of incorrect information but fails to investigate or correct it.
All three situations could cause concern, but they involve different conduct and potentially different legal consequences. A proportionate approach should distinguish the original error from any subsequent failure to address it. The existence of a policy concern does not, without more, establish a breach of binding law.
The same caution applies to section 233 of the CMA. It should not be described as making every false AI-generated answer an offence. Responsibility depends on the applicable statutory requirements and the evidence concerning the relevant person's conduct. Any proposed guidance or policy reform should be presented as supplementary to that legal analysis, not as a substitute for it.
1.2 The 2026 communications-regulatory amendments
The Malaysian Communications and Multimedia Commission (Amendment) Act 2026 (Act A1799) came into operation on 14 October 2026. As enacted legislation, it forms part of Malaysia's binding legal framework. Among its changes are functions relating to standards for the safety, security, integrity and reliability of information assets and communications services, as well as the review or audit of specified information and activities [7].
These provisions are relevant to the institutional context in which additional safeguards might be developed. They do not, by themselves, establish a universal legal duty requiring every AI model to provide factually correct election answers. The applicability of a proposed requirement must be assessed against the amended legislation, any valid subsidiary instruments or regulatory directions, and the service concerned.
The separate Communications and Multimedia (Amendment) Act 2026 (Act A1798) principally amends section 202 of the CMA in relation to universal-service initiatives involving national security. It should not be presented as a general AI-liability statute [8].
The distinction matters. A proposal can be sensible as a matter of policy without necessarily falling within an existing regulator's legal authority. Similarly, a regulator's statutory function may support further rule-making or oversight without itself resolving every question of liability for an inaccurate AI output.
1.3 Malaysia's proposed AI Governance Bill
Malaysia's proposed AI Governance Bill adds another layer to this discussion, but it is not, at the date of this analysis, enacted law. Its public consultation ran from 10 July to 1 August 2026. The official consultation record identifies the process as closed and at the pre-drafting stage [4, 5].
The proposed framework is intended to establish central oversight, risk-based governance requirements and clearer responsibilities for AI actors. The Ministry of Digital has also indicated that the proposed Bill is not intended to regulate AI outputs directly; illegal-content issues would continue to be addressed through existing laws and regulatory frameworks [4].
These statements describe a policy direction and consultation position, not binding obligations presently enforceable against all AI actors. The final scope, legal effect and institutional powers would depend on the text enacted by Parliament and any subsequent regulations, codes or guidance.
This creates a useful policy question: can system-level safeguards improve the reliability of AI-generated election information without turning AI governance into a general mechanism for controlling political speech?
A possible approach would be to require defined services, where legally authorised and proportionate, to demonstrate how they verify critical factual information, investigate errors and correct answers. At present, this should be understood as a policy proposal rather than a general existing statutory duty. Whether an individual communication warrants further legal action would remain a separate question under the applicable law.
The objective should be to improve the reliability of the process, not to assume that every inaccurate output deserves the same response.
2. Japan's latest measures: an important regional development
Japan's latest initiative is particularly relevant because it addresses how election-related information is presented and distributed on large social-media platforms. It should, however, be separated into its binding legislative component and its non-binding implementation material.
The legal status needs to be stated carefully. Japan's Act Partially Amending the Public Offices Election Act and the Act on Measures against Infringement of Rights, etc. Arising from the Distribution of Information through Specified Telecommunications was promulgated as Act No. 58 of 2026 on 17 July 2026. The relevant amended provisions are scheduled to take effect on 1 March 2027 [22, 23]. The Act is enacted legislation, but the relevant provisions are not yet in force as at 23 October 2026.
On 23 October 2026, Japan's Ministry of Internal Affairs and Communications (MIC) announced a public consultation on draft guidelines intended to support the effective implementation of measures to mitigate adverse effects on electoral fairness. The consultation is scheduled to run from 24 October to 24 November 2026. The detailed guidance is therefore still a draft at the date of this analysis and should not be described as binding law or as evidence of settled implementation practice [22].
2.1 What is Japan proposing?
The draft guidelines and associated legislative materials address several aspects of the online information environment [22, 23]. The amended legislation supplies the binding legal framework, while the draft guidelines indicate how the Japanese authorities may expect covered operators to implement or explain relevant measures. The latter may be revised following consultation and should therefore be treated as proposed guidance rather than final regulatory requirements.
Prioritising reliable information. The proposed implementation approach would allow platforms to give greater visibility to information from official websites, candidates, political parties and other sources considered reliable. This is a proposed platform practice within the legislative and guidance framework, not a legal determination that every official statement is correct.
Labelling AI-generated material. The amended election law provides for labelling specified AI-generated or modified images and videos distributed online in covered election contexts, subject to the statutory conditions and exclusions. This is the clearest example in this section of a binding legislative requirement, although its practical operation will depend on the statutory text, commencement and any applicable implementation arrangements.
Addressing financial incentives. Proposed platform measures include suspending monetisation for qualifying election misinformation that could harm electoral fairness, as well as addressing accounts and content that generate revenue. These measures should be distinguished from the statutory labelling provisions: their precise legal status and implementation depend on the enacted provisions and the final guidance.
Responding to coordinated abuse. The proposed measures also address bot-driven activity, account transparency, warnings about synthetic media and cooperation with election-related stakeholders. These are elements of the legislative scheme and draft implementation approach, but their exact obligations should not be inferred beyond the enacted text or treated as final until the consultation process is complete.
Public reporting. The amended platform law requires covered large-scale platform operators to take necessary measures appropriate to their service characteristics and to publish information about the measures they implement annually [23]. This is an enacted statutory obligation, subject to its scope, commencement and the conditions specified in the law.
The approach is significant because it addresses more than whether an individual post is true or false. It also examines how content is promoted, whether misleading material generates revenue, and whether platforms can demonstrate the measures they take.
In plain language, Japan is trying to make it harder for misleading election information to dominate what people see online, while making it easier to find material from sources considered reliable. That description captures the policy objective, but it should not be mistaken for a single universal legal duty applying to every service or every item of election information.
That does not mean the government has proved that every official statement is correct or that every alternative source is unreliable. Nor does the proposed approach require every disputed political statement to be removed. The legislation and draft guidance must be read in the context of their scope, implementation requirements and protections for legitimate expression. The enacted provisions are binding once in force; the draft guidance remains subject to consultation and possible revision.
2.2 How does this compare with my earlier proposal?
There is a genuine similarity between Japan's proposal and the mechanism discussed in my earlier article: both recognise the importance of reliable sources when people seek election information.
The difference is where each approach intervenes and what legal status each component has.
Japan's enacted and proposed measures are principally concerned with the wider information environment: what platforms display, how they handle synthetic media, what incentives they provide and how they respond to misinformation. The statutory provisions scheduled to take effect in 2027 should be analysed as future binding law, while the MIC consultation document should be treated as draft guidance that may inform implementation but is not yet final.
My earlier proposal focuses more narrowly on the information used to generate a particular AI answer. It suggests a privacy-conscious, read-only SPR data interface for defined election facts, supported by source links, update timestamps, version information, reporting and correction procedures [15]. This remains a research and policy proposal, not an existing Malaysian legal requirement or government system.
In plain language, Japan's proposed approach is like helping people find the most reliable signposts in a crowded public square. My proposal is like checking the original timetable before giving someone a travel time. The first helps people find dependable information; the second checks whether a particular answer agrees with the relevant record. Japan's approach is a comparative example of legislative and regulatory design; the Malaysian mechanism is a proposed application of accountability principles.
These are complementary functions. A platform might promote an official election website without guaranteeing that an AI assistant has retrieved the correct information or accurately reflected it in an answer. Conversely, a well-designed election-data interface would not, by itself, prevent bot campaigns, manipulated candidate videos or monetised misinformation from spreading across social media.
The comparison therefore supports a limited conclusion: my mechanism is more specific to the verification and correction of AI-generated factual answers, while Japan's proposed measures address a broader set of platform-level election risks. This does not establish that one approach is more effective overall, and the proposed Malaysian mechanism has not yet been empirically evaluated. Nor does Japan's example, whether enacted or still in draft form, establish that Malaysia has adopted or is legally required to adopt an equivalent model.
2.3 What Malaysia can learn from Japan
Japan's approach, considered as a combination of enacted legislation, forthcoming implementation and draft guidance, suggests that election integrity may require several distinct responses rather than one universal rule. It is a comparative example from which Malaysia may draw policy lessons, not a source of binding obligations in Malaysia.
Where the problem is an incorrect polling date generated by an AI assistant, authoritative retrieval and output validation may be appropriate. In Malaysia, these would presently be safeguards to be developed through policy, procurement, service design or future legislation, unless an existing legal instrument clearly requires them in the particular context.
Where the problem is a realistic synthetic video falsely depicting a candidate, labelling requirements and rules governing election campaigning may be more relevant. Japan's enacted provisions provide a regional example of how such risks may be addressed, but their scope and operation should not be assumed to apply in Malaysia.
Where the problem is coordinated distribution or financial incentives for misinformation, platform-level measures may be needed. Japan's legislative framework and draft guidance illustrate possible approaches, while Malaysia would need to identify the relevant statutory authority and decide whether any comparable measures should be proposed.
Where the problem is deliberate deception, the applicable electoral, communications or criminal law must be assessed separately. A comparative policy proposal or draft guideline cannot itself establish criminal liability in Malaysia.
The important lesson is to identify the type of problem and the point at which intervention can reasonably prevent or remedy it. A rule designed for platform amplification should not automatically be treated as a solution to AI factual errors, and a data-verification mechanism should not be expected to replace measures addressing deceptive campaign media.
Figure 1. Two complementary approaches to election-information reliability.
Japan's proposed approach focuses on the visibility, labelling and distribution of election-related content. The Malaysian proposal focuses on checking critical facts before an AI system answers and correcting errors when they occur. The Malaysian diagram represents a research proposal, not an existing government system.
3. Other regional lessons
Japan is not the only relevant comparator. Singapore, South Korea and ASEAN provide different ways of thinking about correction, transparency and shared responsibility.
3.1 Singapore: correcting false information
Singapore's Protection from Online Falsehoods and Manipulation Act 2019 (POFMA) permits correction directions in qualifying circumstances involving false statements of fact. Its operation and criminal provisions have distinct legal requirements [10].
Singapore also introduced election-specific restrictions concerning certain realistic but false representations of candidates in online election advertising [11].
The lesson for Malaysia is not to copy Singapore's legislation wholesale. It is to recognise that correction, removal and criminal prosecution are different interventions.
For example, if a service accidentally provides an incorrect polling date, a prompt correction may be the most appropriate first response. If an actor deliberately uses AI to deceive voters, a different legal assessment may be required.
3.2 South Korea: transparency and defined AI duties
South Korea's AI Basic Act entered into force on 22 January 2026. It establishes binding transparency requirements for covered generative-AI products and services, alongside other role- and risk-related duties [12].
South Korea also has election-specific restrictions concerning covered deepfake material used in election campaigning [13].
These mechanisms show that general AI governance and election law can address different aspects of the same problem. A transparency label tells a user that material is AI-generated; it does not establish that the information is correct. Factual verification and content labelling should therefore not be treated as substitutes for one another.
3.3 Japan: platform responsibilities and practical guidance
Japan's proposed measures complement its broader AI-governance framework and other existing laws [14]. Their significance for Malaysia lies in the way they link platform responsibilities to the characteristics of the service while addressing election-specific risks.
However, the relevant election guidelines remain under consultation as at 23 October 2026. Their final wording and implementation should be examined before drawing conclusions about how they operate in practice.
3.4 ASEAN: shared responsibility
ASEAN's AI Governance and Ethics Guide and expanded generative-AI guide recommend shared responsibility, testing, assurance, incident reporting, security and content provenance [2, 3].
These principles are important prior policy work. The present proposal should not claim to originate the idea that multiple actors should contribute to responsible AI deployment.
Its potential contribution is narrower: to examine how these principles can be applied to critical election facts in Malaysia through clearer source-verification, output-validation and correction arrangements.
4. A practical proposal for Malaysia
SPR already operates an official open-data portal containing election-related information, including results, candidates, party information, voter statistics and constituency-related datasets [15].
This provides a starting point. Before mandating a new API, policymakers should assess the existing datasets, their update frequency, their metadata and the availability of documented interfaces for the particular information needed by voters.
A possible assurance mechanism would have four stages.
Stage 1: Use authoritative information
For defined facts such as polling dates, locations and official procedural requirements, the system should identify an appropriate authoritative source and the relevant version of the information.
Stage 2: Check the answer
The system should verify that the retrieved record supports the final answer. Where practical, critical structured facts should be rendered directly from verified data rather than generated solely from model memory.
Stage 3: Show the source
The answer should provide a source link and meaningful information about the currency of the record. A user should be able to check where the answer came from.
Stage 4: Report and correct errors
A service should provide a usable reporting mechanism. Where an error is confirmed, the relevant organisation should investigate, correct or withdraw the answer as appropriate, and record the corrective action.
In everyday terms, this is similar to a newsroom checking a date against an official announcement before publishing it. The difference is that an AI service may generate thousands of answers through automated processes, so checks need to be built into the system and tested rather than left entirely to individual users.
These proposed measures should be proportionate to the function and risk of the service. A general-purpose chatbot, a specialist voter-information service and a social-media platform do not necessarily have the same duties or degree of control.
A mandatory SPR interface is one possible implementation, but it should not be presumed to be the only acceptable approach. Equivalent methods could be considered if they demonstrate comparable reliability and traceability.
5. Responsibility, privacy and freedom of expression
The proposed process must not assume that all failures have one cause or one responsible actor.
If an official record is outdated, the investigation should examine the source and whether the service had appropriate freshness controls. If the data are correct but the retrieval system obtains the wrong record, the integration process becomes relevant. If the service receives a credible error report and does nothing, that subsequent conduct should be assessed separately.
More than one actor may have relevant responsibilities. Any legal consequences must depend on the applicable duties, statutory authority and evidence—not merely on which service was last seen by the voter.
The Malay proverb “Berat sama dipikul, ringan sama dijinjing” is recorded in as expressing the idea that burdens and responsibilities are shared. It offers a familiar way to explain why election authorities, AI providers, system integrators and publishers may each have a role in maintaining reliable voter information. Shared responsibility, however, should not mean that responsibility becomes vague or indiscriminate: each actor’s duties should still depend on the applicable law, its actual control over the relevant process and its capacity to prevent or correct a failure.
Privacy also matters. Election-information systems may process user queries, account information and interaction logs even if the answer itself contains only public facts. Malaysia's PDPA and its applicable exceptions must be examined in relation to each organisation and processing activity. The proposed AI and Personal Data Protection Framework is a separate policy development that also warrants consideration [17].
Cybersecurity presents another distinct question. A compromised source, altered record or disrupted service requires different controls from a model that misinterprets correct information. Applicable cybersecurity duties should be considered where relevant, without assuming that every election dataset or AI service falls within a particular statutory designation.
Finally, reliability requirements must not become a general mechanism for restricting political debate. An official polling date is a verifiable administrative fact. Political opinions, criticism of candidates and contested interpretations of policy raise different questions.
UNESCO's Guidelines for the Governance of Digital Platforms emphasise that addressing online harms must be balanced with freedom of expression and access to information [16]. Any Malaysian proposal should therefore define the relevant factual problem, the evidence needed to establish non-compliance, the authority to act and the available review mechanisms.
Official sources should be accessible and verifiable, but not immune from scrutiny or correction.
6. How should the proposal be evaluated?
It would be premature to claim that an SPR data interface or source-verification protocol will necessarily eliminate hallucinations or prevent election misinformation. These are proposals whose effectiveness needs testing.
A practical evaluation could examine whether the system:
gives accurate answers to questions about polling dates and locations;
1. Retrieves the correct, current source;
2. Produces answers supported by the cited record;
3. Abstains when information is unavailable or conflicting;
4. Allows users to report errors successfully; and
5. Corrects verified mistakes within a time appropriate to their seriousness.
Testing should include supported Malaysian languages and different question styles. Performance should be compared with a baseline system that does not use the proposed controls.
The results would help determine whether the additional safeguards improve reliability, how much they cost to implement and which requirements are justified for different services.
Japan's proposed measures should also be evaluated separately. Source prioritisation, synthetic-media labelling, monetisation controls and platform transparency target different risks; their effectiveness should not be assumed from their adoption alone.
Conclusion
Japan's latest election-related measures are a relevant development for Malaysia. They reinforce the importance of making reliable information easier to find, improving transparency around certain AI-generated content and requiring covered platforms to take appropriate measures against risks to electoral fairness.
There is a clear similarity with my earlier article, but the mechanisms are not identical. Japan's proposed approach addresses the broader distribution and presentation of election-related information. My proposal focuses on verifying critical facts before an AI assistant answers, preserving source information and providing a route to correction.
The two approaches can complement one another. Better visibility of official information does not guarantee that every AI-generated answer is accurate, while a reliable data interface cannot by itself prevent coordinated misinformation or manipulated campaign media.
For Malaysia, the practical task is to assess existing SPR data infrastructure, identify the legal basis for any new obligations and determine which safeguards are justified by evidence. The CMA, ONSA, election law, data-protection framework and proposed AI Governance Bill have different functions; their relationship should be examined carefully rather than assuming that one instrument can solve every problem.
The proposed relay-race approach is best understood as an application of established accountability principles to a specific election-information problem. Its value will depend on whether it makes errors easier to detect, attribute and correct while preserving legitimate political expression.
The aim is not to promise error-free AI. It is to make critical election information more reliable, make failures easier to remedy and ensure that accountability follows the evidence.
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