What are ethical issues of using WhatsApp
Executive summary
WhatsApp's popularity belies a thicket of ethical tensions: robust end-to-end encryption protects message content in transit but leaves metadata, backups, AI interactions and platform design open to exploitation, regulatory scrutiny and misuse [1] [2] [3]. The EU’s designation of WhatsApp as a Very Large Online Platform under the Digital Services Act forces the company to balance user privacy against duties to curb illegal and harmful content—creating sharp trade‑offs and new ethical questions about surveillance, consent and institutional responsibility [4] [5].
1. Privacy theatre versus real limits of encryption
WhatsApp emphasizes that ordinary chats are end‑to‑end encrypted so even the company cannot read them, but multiple analyses warn that this protection is partial: metadata about who communicates with whom, backups stored outside E2E protection, and potential subpoenaed cloud backups expose content and context to third parties [1] [2] [6].
2. Metadata as a power law problem
Even when message bodies are encrypted, the platform collects rich metadata—who is in which group, when messages occur and association graphs—that can be profoundly revealing for surveillance, profiling and inference; privacy commentators and fact‑checks flag this as a major ethical blind spot often downplayed in public messaging about “encryption” [1] [6].
3. Backups, cloud storage and the single point of decryption
Encrypted backups are optional and, when not used, chats stored in cloud services become decryptable if obtained by a provider or compelled by law; authorities, regulators and privacy reviews have all noted that backups are an Achilles’ heel that can nullify end‑to‑end guarantees in real investigations [2] [7].
4. Meta AI, feature creep and new data flows
Integration of Meta AI into WhatsApp has introduced additional ethical vectors: interactions routed to AI services may lack the same E2E protections and feed model training, raising consent and transparency questions about how conversational inputs are used and whether users understand those trade‑offs [3] [8].
5. Regulation, content duties and freedom of expression tensions
With Channels pushing WhatsApp above the EU DSA threshold, the platform must now take stronger action against illegal and harmful content and assess systemic risks such as electoral manipulation—obligations that may pressure more intrusive moderation, automated screening or metadata analysis, and create tensions between safety and private communications [4] [5] [9].
6. Accountability, oversight and contested claims
Regulatory probes and legal challenges complicate the ethics landscape: Ofcom has opened investigations into Meta’s information about WhatsApp (raising oversight questions), and class‑action litigation accuses the company of misleading encryption claims while WhatsApp denies the allegations, illustrating disputes over corporate transparency and the burden of proof for privacy promises [10] [7] [11].
7. Professional uses, consent and boundary erosion
In sectors like healthcare, WhatsApp’s informality creates ethical hazards: clinicians using the app face obligations to obtain informed consent, protect confidentiality and maintain professional boundaries, yet research warns that norms and regulation lag behind practice, making harm to patients a realistic risk [12].
8. Research ethics and civic harms
Scholars studying WhatsApp note that encryption and group dynamics produce “perceived secrecy” that both enables civic engagement and complicates ethical research; the same properties that shelter dissent can also facilitate misinformation or coordinated harm, forcing complex judgments about researcher responsibility and platform governance [13].
Conclusion: unavoidable trade‑offs and the need for clearer consent
The ethical landscape around WhatsApp is not a single failure but a series of trade‑offs—between content privacy and metadata exposure, platform safety and private speech, innovation (AI features) and user consent—now sharpened by DSA obligations and regulatory scrutiny; resolving them will require clearer, enforceable transparency about data flows, default protections for backups and AI interactions, and stronger oversight of how metadata is stored, accessed and shared [4] [3] [6].