The recent disturbances to OpenAI’s ChatGPT service, reportedly resulting from a cyberattack attributed to Anonymous Sudan, have ignited significant apprehensions within the AI community. The concept of ‘knowledge slaveries’ raises a pivotal question: Can a Bottom-up AI approach offer a viable solution to the challenges arising from the growing dependence on AI systems?
The recent interruption of OpenAI’s ChatGPT service, occurring on November 8, has triggered concerns across the AI and natural language processing communities. With over 100 million active weekly users, ChatGPT, a stalwart in the AI landscape, experienced an unexpected blackout lasting over 90 minutes. The repercussions extended beyond ChatGPT, affecting OpenAI’s entire ecosystem as its API services also succumbed to the disruption.
The disruption of ChatGPT and its associated services has drawn attention not only due to its duration and extent but also because it marked the second outage within a 48-hour timeframe. A partial outage occurred on November 7, following the one on October 19 and the previous one on September 15. These partial outages, along with the latest major one, raise concerns about the service’s stability, reliability, and the potential impact of future outages on global business development.
OpenAI, a pioneering company in AI innovation, has been actively addressing this issue. They’ve implemented a fix and restored ChatGPT service, assuring users of their commitment to swiftly and effectively resolve the problem. However, according to the latest updates from the OpenAI status website, the company is ‘dealing with periodic outages due to an abnormal traffic pattern reflective of a DDoS attack’ and is continuing to work to mitigate similar issues.
In a recent development, the hacktivist group Anonymous Sudan has claimed responsibility for the cyberattack on OpenAI’s ChatGPT. The group outlined its motives in a post on their Telegram channel, citing OpenAI’s collaborations with Israel as a primary reason for targeting ChatGPT. Anonymous Sudan emphasized its focus on American companies as a driving force behind the attack and claimed an alleged bias in ChatGPT, suggesting a preference for Israel over Palestine in the chatbot’s interactions. These stated reasons reveal the complex motivations behind the cyber assault, intertwining geopolitical concerns and perceived biases within the AI realms.
These unexpected outages have prompted many users to question the sustainability of such backing infrastructure, as many companies increasingly adopt ChatGPT’s services to support their daily tasks. The trajectory of AI adoption across various industry sectors is poised for significant growth from 2022 to 2025. In 2022, nearly half of the surveyed executives anticipated wide-scale adoption of AI technologies in their respective companies, underscoring the recognition of AI as a transformative force within the global economy.
Looking ahead to 2025, industry leaders express even more optimism, anticipating not only continued growth in AI adoption but surpassing earlier projections for wide-scale implementation. Executives envision a future where AI becomes not just a supplementary tool but a critical component deeply embedded in the operational fabric of their companies.
This shift in expectations from wide-scale to critical implementation reflects a growing understanding of the profound impact that AI can have on the global economy workflow. AI is increasingly seen as an integral element driving efficiency, innovation, and strategic decision-making.
The factors driving this anticipated surge in AI adoption within the global work environment are diverse. The promise of enhanced data analysis, streamlined processes, and the ability to derive actionable insights from vast datasets position AI as a catalyst for operational excellence. Additionally, as AI technologies mature and demonstrate tangible benefits, companies are more inclined to invest in and fully embrace these advancements.
The increasing integration of AI tools into various aspects of personal and professional lives raises questions about the possibility of working and living without their support in the near future. Once accustomed to automated processes, overcoming longer inaccessibilities and malfunctions may prove challenging. Analyzing this scenario requires considering the current role of AI, its impact on different sectors, and potential future developments, as the recent outage of OpenAI’s services highlighted the need for stronger infrastructure and consistent service reliability.
The continual use of AI services exposes our thoughts and emotions through interactions with AI platforms, generating vast amounts of data that can be used to extract patterns in our thinking. This trend has given rise to a new AI economy where these patterns are collected, codified, and monetized, raising concerns about privacy and cognitive intrusions beyond what social media and tech platforms currently pose.
This development risks creating a state of ‘knowledge slavery,’ where corporate or government AI monopolies control access to our knowledge. To counter this, it is essential to retain ownership over our thinking patterns, including those derived automatically through AI.
One possible solution lies in the development of Bottom-Up AI, as suggested by Diplo’s Executive Director, Dr. Jovan Kurbalija. Bottom-Up AI is both technically feasible and ethically desirable, with the potential to address governance concerns raised by generative AI tools like ChatGPT. It gives control back to individuals and communities, ensuring privacy and data protection, and fosters inclusivity, innovation, and democracy by mitigating the risks of power centralization inherent in generative AI.
Contrary to the prevailing belief that powerful AI platforms can only be built using big data, leaked documents from Google suggest that open-source AI could outperform proprietary models like ChatGPT. Open-source platforms such as Vicuna, Alpaca, and Llama are already offering similar quality while being more cost-effective, faster, more modular, and greener in terms of energy consumption.
The technology for Bottom-Up AI is advancing, but there is a need to ensure the quality of data. Currently, data labeling is mainly performed manually in low-cost English-speaking countries, risking labor law and data protection challenges. Diplo, a leading organization, integrates data labeling into their daily operations, gradually building Bottom-Up AI by digitally annotating text during research and other tasks.
While the full adoption of Bottom-Up AI remains uncertain, it may coexist with top-down AI approaches. Some individuals and communities may be more inclined to experiment with and embrace Bottom-Up AI, while others stick to top-down AI due to inertia. However, questioning the prevailing AI paradigm and exploring alternatives is crucial to make informed decisions that benefit society as a whole and to prevent inconveniences from future outages of bigger AI service providers people are relying on.