Is ChatGPT Becoming the Ultimate Super App? Unpacking the Ambitions and Responsibilities of AI

 Is ChatGPT Becoming the Ultimate Super App? Unpacking the Ambitions and Responsibilities of AI

As artificial intelligence (AI) technologies rapidly evolve, their integration into daily life grows increasingly seamless and far-reaching. OpenAI’s ChatGPT, once a text-based conversational agent, is now positioned at the vanguard of this transformation, aspiring to become an all-encompassing “super app.” With features ranging from managing correspondence and assignments to facilitating shopping and payments, ChatGPT’s trajectory prompts both excitement and profound concern. The ambition to centralize digital life around a single AI platform raises questions not only about convenience and innovation, but also about the ethical, legal, and accountability frameworks necessary to safeguard users. This research paper explores the rise of ChatGPT as a super app, critically examines the implications of its expanding reach, and interrogates the responsibilities that must underpin such technological advances, drawing on recent interdisciplinary scholarship on AI accountability and governance.

The Rise of ChatGPT as a Super App

The evolution of ChatGPT from a simple chatbot to a super app signals a paradigm shift in digital user experience. Most notably, the introduction of the Instant Checkout feature allows users to make purchases directly through the AI interface, bypassing traditional e-commerce workflows. This innovation has garnered enthusiasm from both consumers and investors, evidenced by significant market responses such as a 16% increase in Etsy shares and a 4.5% rise for Shopify following the announcement (see essay prompt). The promise of streamlined, fee-free shopping encapsulates the super app vision: a frictionless, integrated environment where diverse needs are met within a single application.

Furthermore, OpenAI’s development of ChatGPT Pulse—an engine for personalized news and daily updates—positions the platform as a potential hub for information, productivity, and consumption. By encouraging users to begin their day with ChatGPT, OpenAI advances the dream of a unified digital gateway, reminiscent of super apps that have transformed markets in Asia.

However, the pursuit of seamlessness and convenience is not without risks. As AI systems like ChatGPT aggregate functionalities, they also aggregate power and responsibility, necessitating robust mechanisms for risk mitigation and accountability (Nguyen et al., 2024; Ojewale et al., 2025).

The Allure and Peril of Integration

Seamlessness and User Experience

The drive toward integration is fueled by the desire for simplicity and efficiency. With features such as Instant Checkout, users avoid lengthy checkout procedures and hidden fees, while merchants potentially benefit from increased conversion rates and reduced friction. OpenAI’s approach mirrors broader industry trends toward “one-stop” platforms, aiming to embed AI into every facet of daily life (see essay prompt).

Yet, as ChatGPT becomes a locus for communication, commerce, and information, it also amasses unprecedented influence over user behavior and decision-making. This centralization raises questions about data privacy, algorithmic transparency, and the potential for abuse of power—issues that are not easily resolved by technical innovation alone (Nguyen et al., 2024).

Expanding Functionalities and Personalization

ChatGPT Pulse exemplifies the push toward hyper-personalization, with AI systems curating content and updates tailored to individual user profiles. While personalization can enhance relevance and engagement, it also introduces risks of filter bubbles, manipulation, and biases embedded in algorithmic design (Birhane et al., 2024). In this context, the boundary between user empowerment and algorithmic control becomes increasingly ambiguous.

Accountability and Responsibility in the Age of AI Super Apps

Legal and Ethical Hurdles

The expansion of ChatGPT’s capabilities has been accompanied by high-profile controversies. Lawsuits related to harmful advice and tragic outcomes—such as the wrongful death suit following a teenager’s interaction with ChatGPT—underscore the real-world stakes of AI deployment (see essay prompt). These incidents have catalyzed calls for greater accountability, both from developers and from the institutions that govern AI systems.

Recent scholarship highlights the complexity and multidimensionality of AI accountability. As Nguyen et al. (2024) observe, accountability in AI is often reactive, triggered by reputational damage or scandal. This emphasis on sanctions and punishment can foster a negative connotation, overshadowing opportunities for proactive, virtuous engagement by developers and organizations.

Parental Controls and the Burden of Oversight

In response to safety concerns, OpenAI has introduced parental controls that allow guardians to monitor and restrict their teenagers’ interactions with ChatGPT. While such measures may provide a first line of defense, they also shift responsibility from technology providers to users and their families—echoing patterns observed in other technology domains (see essay prompt). This burden-sharing approach is insufficient without systemic safeguards and proactive accountability mechanisms (Nguyen et al., 2024).

The Limits of Technical Solutions

OpenAI’s implementation of Safe Completions in GPT-5 represents an attempt to embed safety features directly into the AI’s architecture. However, as acknowledged by the company, these systems are not foolproof and may fail during sensitive conversations. The challenge is compounded by the inherent opacity and complexity of large language models, which complicate efforts to audit, explain, and regulate their outputs (Ojewale et al., 2025; Nguyen et al., 2024).

Towards Proactive AI Accountability

Rewarding Proactive Behavior

A recurring theme in recent research is the need to move beyond punitive approaches to AI accountability. Nguyen et al. (2024) argue that while sanctions are necessary, they often result in reactive, minimal compliance rather than genuine engagement. By contrast, reward-based mechanisms—such as bug bounties for identifying algorithmic bias—can foster intrinsic motivation among developers to anticipate and address risks proactively. Drawing on Self-Determination Theory, the authors suggest that competence, autonomy, and relatedness are key drivers of proactive accountability behavior.

Incentivizing transparency, documentation, and self-initiated risk mitigation can create a culture of responsibility that complements regulatory oversight. However, as Nguyen et al. (2024) caution, rewards must be carefully designed to avoid undermining intrinsic motivation or devolving into box-checking exercises.

Infrastructure for Auditing and Oversight

Effective AI accountability also depends on the availability of robust auditing tools and institutional infrastructure. While the proliferation of toolkits for fairness, explainability, and performance analysis is encouraging, Ojewale et al. (2025) note that existing resources often fall short in supporting the full scope of accountability. Auditors face barriers in accessing data, standardizing practices, and communicating findings—particularly in external, independent evaluations.

To address these gaps, Ojewale et al. (2025) recommend the development of comprehensive, interoperable infrastructure that supports not only evaluation, but also harms discovery, advocacy, and iterative feedback. This vision moves beyond isolated tools toward a systemic approach to AI governance.

Multidimensional Accountability Across Disciplines

The conceptual ambiguity surrounding AI accountability is exacerbated by disciplinary fragmentation (Nguyen et al., 2024). Computer science, law, and information systems each bring distinct perspectives and priorities, from technical frameworks and legal compliance to behavioral effects on individuals and organizations. Synthesizing these dimensions is essential for developing unified standards and expectations.

Accountability, as defined by Bovens and contextualized by Wieringa, is a relationship in which actors must explain and justify their conduct to a forum empowered to judge and impose consequences (Nguyen et al., 2024). In the context of AI super apps, this implies the need for clear identification of responsible actors, transparent processes for deliberation, and enforceable mechanisms for redress and improvement.

Governance and the Case of AI Super Apps

The governance challenges posed by AI super apps like ChatGPT are not unique. Analysis of other foundational models, such as Anthropic’s Claude, reveals similar concerns regarding transparency, benchmarking, and data handling (Priyanshu et al., 2024). Effective governance requires alignment with frameworks such as the NIST AI Risk Management Framework and the EU AI Act, which emphasize risk mapping, stakeholder engagement, and continuous adaptation.

Priyanshu et al. (2024) highlight the importance of translating ethical principles into practicable governance processes, cautioning against one-size-fits-all approaches that may suppress diversity or entrench bias. As AI systems become central to digital life, ongoing stakeholder collaboration and public input are critical to maintaining legitimacy and social trust.

Conclusion

The ascent of ChatGPT as a candidate for the ultimate super app encapsulates both the promise and peril of AI’s integration into society. While the allure of seamless, personalized, and efficient digital experiences is undeniable, the concentration of power and the potential for harm demand vigilant, multidimensional accountability. As recent scholarship underscores, true progress in AI requires not only innovation, but also a proactive, inclusive approach to governance and responsibility.

Developers, organizations, and regulators must work collaboratively to build infrastructures that support transparency, auditing, and stakeholder engagement. Incentives for proactive behavior, robust technical safeguards, and clear lines of accountability are all necessary components of a safe and equitable AI ecosystem. Above all, the evolution of super apps like ChatGPT must be guided by the principle that innovation without responsibility is not genuine progress, but a pathway to exploitation and harm.

As AI technologies continue to weave themselves into the fabric of everyday life, upholding high standards of accountability and ethical development is both a moral imperative and a practical necessity. Only by embracing these responsibilities can we ensure that the benefits of AI are realized without sacrificing the safety, autonomy, and dignity of users.

References

Birhane, A., Steed, R., Ojewale, V., Vecchione, B., & Raji, I. D. (2024). AI auditing: The Broken Bus on the Road to AI Accountability. http://arxiv.org/pdf/2401.14462v1

Nguyen, L. H., Lins, S., Du, G., & Sunyaev, A. (2024). Exploring the Impact of Rewards on Developers’ Proactive AI Accountability Behavior. http://arxiv.org/pdf/2411.18393v1

Nguyen, L. H., Lins, S., Renner, M., & Sunyaev, A. (2024). Unraveling the Nuances of AI Accountability: A Synthesis of Dimensions Across Disciplines. http://arxiv.org/pdf/2410.04247v2

Ojewale, V., Steed, R., Vecchione, B., Birhane, A., & Raji, I. D. (2025). Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling. http://arxiv.org/pdf/2402.17861v3

Priyanshu, A., Maurya, Y., & Hong, Z. (2024). AI Governance and Accountability: An Analysis of Anthropic’s Claude. http://arxiv.org/pdf/2407.01557v1