12 AI and digital predictions for 2024
2024 will be the year of AI. AI technology will continue to grow deeper through powerful foundational models and wider through more connections to the rest of the digital ecosystem (e.g. IoT, virtual reality, and digital infrastructures). Smaller AI and open-source models will gain traction for their transparency, adaptability, and eco-friendliness.
AI risks will dominate the governance and regulatory debate. Existing risks (e.g. jobs, misinformation, biases) will receive more attention than existential risks. AI governance will become more specific and concrete, addressing computational power, data and knowledge, algorithms, and AI applications.
The push for national sovereignty over data, AI, and technology infrastructure will reshape digital geopolitics. The digital decoupling between China and the USA will accelerate significantly in 2024. India, Brazil, South Africa, Singapore, Türkiye, and Gulf states, among others, will try to carve an asymmetric ‘third digital space’ between the two superpowers.
There will be a push for new organisations, commissions, and expert groups dealing with AI and digital governance. The adoption of the UN Cybercrime Convention is anticipated to mark the beginning of global digital governance in 2024. The Global Digital Compact (GDC) will be negotiated, and international bodies, including the UN Security Council, will address digital aspects of conflicts and humanitarian crises.
AI will put diplomacy to the test through the automation of tasks using Large Language Models (LLMs). Diplomacy will need to adapt to increased pressure to negotiate AI and digital topics, extending to areas such as digital governance, health, trade, and human rights.
Cybersecurity will be a significant concern, with a focus on military conflicts in Gaza and Ukraine, emerging threats to digital critical infrastructure, and AI-facilitated theft and illegal activities. The expected adoption of the UN Cybercrime Convention in early 2024 will further shape global cybersecurity efforts.
AI’s impact on human rights, including freedom of expression and privacy, will be on the centre stage, sparking debates on dignity and humanity’s definition. Neurorights, influenced by AI and biotechnological developments, will gain prominence.
AI will accelerate economic changes, from restructuring traditional industries to developing new ones built around AI technology. The primary policy dynamics will be related to the economic consequences of the digital decoupling (or de-risking) between China and the USA, anti-monopolies in AI, taxation of online industries, and digital trade.
The standardisation community will prioritise standards for AI, 6G networks, quantum computing, and other advanced technologies. Multilateral processes will explore technical standards as a soft regulation approach.
The decades-long saga around online encryption will gain new momentum with the debate around on-device scanning of communications for illegal content.
Digital identities will gain importance, with a focus on the Digital Public Infrastructure (DPI) initiative endorsed by the G20.
Elections in over 70 countries will heighten concerns about online content, specifically mis/disinformation through deepfake videos, texts, and sounds, which will accelerate efforts to detect AI-generated content.
AI will trigger innovation in new aspects of inclusion as countries and communities will aim to develop bottom-up AI solutions that reflect their cultural and knowledge heritage.
Read the 12 AI and Digital Predictions for 2024 in full.
AI optimism in geopolitically pessimistic Davos
In the serene backdrop of the Swiss Alps, the World Economic Forum (WEF) in Davos stands as a barometer for the year’s technological zeitgeist. After an exceptionally tech-shy Summit in 2023, AI restored tech optimism in Davos this year. The blueness of the tech sky stands out even more against the gloomy and cloudy global geopolitics. Is this optimistic dose of AI a panacea for global problems, the maturation of AI discourse, or yet another tech sleepwalk?
Optimistic dosage. The 24 AI-centric sessions out of 235 at WEF featured 135 speakers and a flurry of 1,101 arguments, with the majority having a positive tone (600). The WEF AI debates have been rated a solid 8 on DiploAI’s optimism scale. Conversations have revolved around AI’s potential to elevate productivity, combat diseases, and solve environmental crises. The economic forecasts present AI as a trillion-dollar boon, a narrative contrast to AI doomsday scenarios from the spring of 2023.
From extinction to existing risks. The narrative surrounding AI risks has shifted at WEF, with existential risks now viewed as problems humanity can overcome, similar to past technological challenges. Most of the AI risk debate focused on the existing risks of AI misuse, such as misinformation, job losses, and educational reform.
It’s unclear why AI gurus have recalibrated their language at WEF, as their predictions that AI would destroy humanity were made with great conviction last year. Sam Altman’s frank admission, ‘no one knows what comes next [with AI]’, encapsulates the dual nature of this juncture: it’s both alarming and reassuring. The uncertainty voiced by those at the forefront of AI development is concerning. At the same time, it is encouraging that tech leaders speak more frankly about their knowledge of the impact of AI without the fear-mongering of the last year.
IPR and content for AI. The New York Times‘ court case against OpenAI over the use of copyrighted material to train AI models was frequently mentioned in Davos. Traceability and transparency in AI development will be critical for a sustainable and functional AI economy.
AI governance. Last year’s narrative that governance should focus on AI capabilities has given way to a focus on applications. It makes AI less unique and more governable, just like any other technology. This approach, used by the EU AI Act, is also gaining popularity in the USA. The WEF discussions revealed more similarities than differences in the regulation of AI in China, the USA, and the EU.
Open source AI. The stance on open-source AI as an unmanageable risk softened at WEF. Yann LeCun of Meta argued that open-source AI is beneficial not only for scientific progress but also for controlling the monopolies of large AI tech companies and incorporating diverse cultural and societal inputs into AI development. Open-source AI will gain traction in 2024, posing a significant challenge to proprietary software such as OpenAI.
AI and development. According to the UN Secretary-General’s Envoy on Technology, Amandeep Sing Gill, AI will not save the SDGs if current trends continue. This candid assessment was more of an outlier in WEF discussions. For example, there was little discussion of the AI-driven widening of digital divides and the increasing concentration of economic and knowledge power in the hands of a few companies.
The confusion around AI potentials and risks underscores the need for a mature, nuanced conversation on AI’s future. We must navigate the known challenges with agile, transparent, and inclusive regulatory frameworks. The Davos debates have made strides in this direction, aiming to steer us away from a dystopian AI future through informed, balanced dialogue rather than fear.
Browse the reports from WEF’s 2024 annual meeting and the final report from the event.
The intellectual property saga: AI’s impact on trade secrets and trademarks
Within the realm of AI and intellectual property, trade secrets and trademarks present unique challenges and opportunities that require special attention in the evolving legal landscape. This blog outlines the complexities, challenges, and opportunities that define intellectual property rights and obligations, focusing on examples from the EU and US legal frameworks.
US trade secret law safeguards diverse information, such as financial, business, scientific, and technical data, if the owner takes reasonable security measures to maintain secrecy. The information must derive value from not being widely known or easily accessible by others through legitimate means (18 U.S.C. §1839(3)). Requirements related to secrecy exclude trade secret protection for AI-generated outputs that are not confidential, such as those produced by systems like ChatGPT or Dall·E. Nevertheless, trade secret laws seem to be more flexible to safeguard various AI-related assets. Namely, there is no stipulation that a trade secret must be originated by a human being, while AI-generated material is treated like any other form of information, as evident in 18 U.S.C. §1839(4), which defines trade secret ownership.
AI innovators often choose trade secret protections over patents due to ambiguous AI and copyright laws. From the EU perspective, the impending AI Act might require disclosure of AI operations, impacting the viability of trade secret safeguarding in some cases. Clear guidelines for AI trade secrets and defining collaboration obligations are crucial for fostering innovation and protecting business assets.
AI integration transforms trademark protection, expanding from logos to AI-generated content and algorithms. Defining the ‘average consumer’ and determining responsibility in trademark infringement cases pose challenges in AI-driven customer service. There aren’t any known cases addressing AI and liability in trademark infringement. However, the Court of Justice of the European Union (CJEU) ruled in cases like Louis Vuitton vs Google France and L’Oréal vs eBay. These decisions state that Google and eBay cannot be held accountable for trademark infringement unless they are aware and actively involved in the automatic selection that results in trademark infringement. Therefore, if we were to apply these cases in AI systems, AI would be held liable in the EU if the AI provider plays a more active role in potential infringing actions.
The impact of AI on industries highlights the need for flexible intellectual property laws to balance innovation and protection. Legal frameworks must adapt to recognise and safeguard AI-generated innovations, raising questions about authorship and ownership attribution. Policymakers and stakeholders must craft forward-thinking regulations to accommodate AI’s potential while protecting all parties’ rights and interests.
A longer version of this blog first appeared on the Digital Watch Observatory. Read the full version of the blog, and discover part 1 of the blog series, The intellectual property saga: The age of AI-generated content.
The perfect cryptostorm
We watched the new Netflix documentary ‘Bitconned’ on cryptocurrency industry fraud. Read what were the ingredients to create such a perfect storm for victims.
The cryptocurrency and blockchain craze from 2017 to 2021 unfolded in a unique setting. One component amplified the other, multiplying the effect, thus creating a perfect cryptostorm that impacted trust in the industry and caused financial losses.
Bitcoin, often termed the digital gold, stood out as a marvel of human engineering and a one-hit wonder. This led to the emergence of a new payment industry, driven by legacy financial organisations seeking relevance in the digital era.
Simultaneously, the retail investing industry saw an influx of capital, with online trading companies backed by institutional investors posing risks for retail users and consumer protection. Unanswered risks, changes in the financial industry, and inexperienced investors set the stage for a perfect storm, exacerbated by human greed.
The perfect cryptostorm. The Netflix documentary ‘Bitconned’ vividly portrays the summoning of the cryptostorm by companies like Centra Tech. In 2017, Centra Tech raised $25 million for a VISA-backed credit card, only to be revealed as a staged mirage. The court case concluded in 2021, resulting in jail sentences. The documentary, led by Ray Trapani, one of Centra Tech’s key figures, reveals how young scammers raised millions in an ICO with a one-page website.
The cryptostorm persisted for years, culminating in the collapse of FTX, the world’s second-largest cryptocurrency exchange. Companies like Celsius and Luna also faced legal challenges for misusing investor funds.
How did crypto scam companies utilise the above ingredients? By promising the right thing at the right moment. Internet users witnessed the financial sector’s transformation and bitcoin’s success. They could easily be convinced that a new decentralised finance infrastructure is on the verge, which will be supported by the lack of a regulatory framework. At the same time, giving them a fair chance to participate in the industry beginnings and become the new crypto millionaires, which was the main incentive for many. If people behind the open-source cryptocurrency (bitcoin) could create the ‘internet of information’, the next generation of cryptocurrency engineers would surely deliver the ‘internet of money’. However, again, it was false. It was, in fact, a carefully worded money-grabbing experiment.
All the above ideas still stand as a goalpost for further industry developments.
Could this happen again for online financial services? Looking ahead, the likelihood of a recurrence of such large-scale scams within online financial services is slim. Regulatory frameworks have been strengthened, and authorities are better equipped to identify and intervene in fraudulent activities. Moreover, investors have become more discerning and wary of promises that seem too good to be true.
However, the potential for deception remains inherent in any technology-driven industry, as opportunistic actors may continue to exploit societal aspirations for innovation and progress. As such, vigilance and scepticism are essential when engaging with new technologies and investment opportunities, ensuring that users are not misled by false promises or exaggerated claims.
A longer version of this blog first appeared on the Digital Watch Observatory. Read the full version of the blog.