Regulation, Responsibility, and Humanisation: How Will AI In 2024 Mature Itself?

What was evidently a wild landscape this year, these trends will ultimately evolve AI in 2024, making it more regulated, responsible, and humanised.

Regulation, Responsibility, and Humanisation: How Will AI In 2024 Mature Itself?

In 2023, artificial intelligence (AI) witnessed a widespread application across diverse sectors. According to data analysis conducted by Finbold, the top 12 AI companies encountered a remarkable surge in market capitalisation, reaching a cumulative increase of $2.86 trillion from January to November.

Here are a few trends, worldwide, that are going to shape the growth and maturation of AI in 2024.

AI in 2023: A recap

Artificial Intelligence (AI) experienced significant breakthroughs in 2023, with ChatGPT and Bard gaining widespread recognition. Notably, major companies have made substantial investments in AI startups. While Microsoft investing $10 billion in OpenAI and Amazon contributing $4 billion to Anthropic, AI has been the talk of the year.

Prominent AI researchers and CEOs engaged in discussions and debates on the likelihood of achieving Artificial General Intelligence (AGI), capturing headlines and public attention. Recognizing the growing impact of AI, policymakers have taken significant steps towards regulation. The European Union (EU) notably introduced a comprehensive set of policies, marking a pivotal moment in governing this transformative technology. In tandem, the Biden Administration issued an Executive Order outlining 150 requirements for federal agencies, signaling a proactive approach to AI governance.

AI in 2024 will address global challenges

While 2023 was the year of AI developments, 2024 will be the year, where the technology will start maturing to present some real life use cases. Here are how some examples of how AI will address global challenges:

Facing severe threats from climate change and pollution, coral reefs are essential to marine ecosystems. Researchers propose an AI system capable of analysing vast oceanographic data to identify optimal coral restoration sites. By employing machine learning algorithms to assess factors such as water temperature, acidity, and existing marine life, the AI platform aims to predict the survival rate of coral in various locations. Tested on Australia’s Great Barrier Reef, this AI-guided restoration is expected to achieve a previously unattainable success rate, significantly increasing healthy coral coverage and serving as a model for environmental restoration projects worldwide.

In the realm of education, AI is poised to revolutionise personalised learning experiences, addressing the limitations of the traditional one-size-fits-all model. The introduction of AI-powered precision education tools in 2024 will lead to significant improvements in student engagement, conceptual understanding, and knowledge application. AI platforms, equipped with advanced natural language processing and machine learning, will analyse a student’s learning style, pace, and comprehension level. This analysis will inform the tailoring of educational content to create an individually customised curriculum for each student. The application of AI in education is expected to bridge learning gaps, particularly benefiting students who traditionally struggled in conventional classroom settings, setting a new standard for a more inclusive and effective educational system.

Humanising AI in 2024

Major companies like Microsoft, Apple, IBM, Tesla, OpenAI, DeepMind, and SAS are making substantial investments in AI hardware and services, seeking to integrate human-like functionality into AI systems. This push towards humanising AI in business holds the potential to significantly impact operations, enabling leaders to make more accurate, data-driven decisions. The incorporation of human-like features aims to reduce the need for human intervention in AI interactions, particularly evident in the evolution from clunky chatbots to more seamless, intuitive interfaces.

The challenge lies in deploying humanised AI in real-world environments at scale, as highlighted by Dr Iain Brown, head of data science at SAS. Despite the considerable business benefits anticipated from humanised AI, the deployment process poses challenges. Researchers globally are exploring novel approaches, such as using physiological signals to enhance AI’s interaction with humans and developing sentiment-sensing capabilities. Initiatives like creating AI brains that don’t require internet connections for remote or space applications demonstrate the evolving landscape. As society increasingly relies on AI, businesses and researchers must navigate barriers and exercise caution in reorienting AI to more human-like characteristics, ultimately aiming for a more widespread reality of AI humanisation.

Good governance and responsible AI in 2024

According to global experts, transparency and responsible development is the future trajectory of AI. “I predict the rising adoption of large-scale AI models will lead to a shift. We’ll go from talking about global AI governance to forming dedicated bodies focused on it. This might include new agencies or institutes within and across nations,” says Keith Strier, Vice President of Worldwide AI Initiatives at NVIDIA and member of NAIC’s Responsible AI at Scale Think Tank.

Kobi Leins, a global expert in AI, international law, and governance, also emphasises the pivotal role individuals play in shaping the future of AI. As a member of Standards Australia’s IT-043 Artificial Intelligence National Committee, she highlights the increasing importance of governance in the face of rising litigation and widespread adoption of technology by companies.

Multimodal AI in 2024

Multimodal AI is poised to revolutionise user interactions with AI systems by integrating visual, auditory, and textual inputs, creating more natural and intuitive experiences. This approach involves combining data, such as images, text, and speech, with advanced algorithms to make predictions and generate outcomes. Think of multimodal AI as a cognitive process akin to the human brain’s ability to process multiple stimuli simultaneously, forming comprehensive conclusions from various data points.

Several notable applications exemplify the potential of multimodal AI. Microsoft’s DALL·E and DALL·E 2, described as an AI that “draws anything at your command,” employs natural language processing and image-text pairings to rapidly generate diverse images based on textual prompts. Renesas Electronics and Syntiant’s voice control technology, embedded in devices like RoboVacs and security cameras, leverages AI-based IoT systems to enhance real-life situational awareness. United Airlines employs multimodal AI in its customer service, utilising NLX’s tool to interact with passengers via voice assistance for tasks like changing travel plans, checking flight status, and providing accessibility information, showcasing the potential for enhanced customer experiences through automation.