As AI becomes increasingly integrated into our lives, it is important to consider the potential impacts of these technologies and how we can mitigate any risks. In 2024, we will see a growing focus on AI regulation and the development of ethical guidelines for AI development and use.
Additionally, there will be a continued focus on innovation in AI, with new applications for AI emerging in a wide range of sectors. However, there will also be a growing concern about the potential for utilization of AI for malicious purposes, such as cyber warfare and surveillance.
Miguel Sabel, global director of strategy and sustainability at Designit , a global experience innovation company, predicts six major trends and moments regarding the world of AI as we head into 2024.
The intense competition and geopolitical power struggles that unfolded throughout 2023 may persist into 2024. In the midst of this fierce rivalry, insights gained through internal information leaks reveal how industry-leading companies grapple with the challenges of maintaining a sustainable competitive advantage solely through their models. This challenge not only stems from the threat posed by rival corporations but also from the widespread adoption of open-source models.
“In the realm of product and user experience, OpenAI has already pioneered the path for crowdsourced innovation with the rise of user-customised GPTs. A marketplace for these innovations is currently under construction, with the belief that “the best GPTs will be crowdsourced by the community,” Sabel said.
Crowdsourced innovation emerges as a potential avenue to achieve more diverse, contextualized, and problem-specific products. Innovators entering this highly competitive space, backed by investments in the billions, may find cause for optimism. Consider OpenAI at the close of 2022 when ChatGPT was released – a testament to the unforeseen potential that can arise in the rapidly evolving landscape.
In 2023, a pronounced upswing in government initiatives related to AI unfolded, marked by significant events such as the White House Executive Order, the UK AI Safety Summit, and the implementation of the EU’s AI Directive. The international landscape also witnessed increased collaboration, underscored by outcomes from the G7 Hiroshima AI Process, yielding 11 International Guiding Principles to govern AI.
However, these efforts have not been without criticism. Critics would argue that they are primarily driven by geopolitical power fights, heavily influenced by interested doomsayers, and perhaps, insufficiently addressing the current harms to ordinary citizens.
“Looking ahead to 2024, let’s take a different approach – viewing these constraints not as impediments, but as catalysts for creativity. This mirrors the impact of sustainability regulations, which, despite presenting challenges, have also served as incentives.”
“If AI follows the same path as sustainability 2024 will see a huge uplift in the development of new businesses, enriched experiences, and likely, see the groundwork for future competitive advantages being put in place,” Sabel added.
As the metaphorical ‘magic dust’ begins to settle in 2024, the expectations placed on GenAI are reaching new heights. Researchers and industry stakeholders must confront its fundamental limitations, some of which are essential considerations (hygiene factors), while others appear inherent to the current form of GenAI. Issues like copyright infringement, biases, hallucinations, and a lack of traceability stand out as prominent examples.
Furthermore, there’s a growing anticipation for GenAI to deliver on promises of generating billions of dollars in efficiency gains and freeing up thousands of human hours for more valuable activities. This is no small feat and will require a concerted effort to meet these substantial expectations.
“I would like to see progress on these fronts in 2024 and also advocate for the development of a critical perspective that collectively helps us set future expectations. One that shift us from the “move fast and break things” paradigm to a new ethos of “move fast and do better.”
For years, the promise of widespread and transparent artificial intelligence dedicated to human augmentation lingered on the edge of possibility. Initially a notion confined to science fiction, this concept has materialized gradually through the advent of voice assistants, finding varying degrees of success in many homes. Anticipation continues to build with upcoming products like the Humane AI pin, further fueling these expectations.
“Firstly, we can observe how GenAI is defining new experience models. Its novelty requires new interaction paradigms – consider recent developments like co-pilot technology, spatial computing, or ephemeral apps, which were virtually unheard of not long ago. These advancements will bring us closer.”
Even more critically, Gen AI is heightening existing concerns surrounding responsible technology. This is not merely a public apprehension. It also poses a significant challenge within the very companies responsible for designing and building these products. If we are to seamlessly integrate an imperceptible agent into our lives, fostering trust becomes an imperative.
“We find ourselves amidst a significant hype cycle, yet the exact position within the curve remains uncertain. Each new release stirs excitement, yet there’s a growing concern about a potential bubble burst, especially when experts identify a specific decline in the quality of responses of AI tools like ChatGPT due to model changes.
In this dynamic and uncertain environment, the adoption of AI is far from uniform. It’s available for a select group only. This discrepancy is due to disparities in access to essential tools, hardware, and a comprehensive understanding of AI capabilities.
This uneven adoption landscape may persist, even as AI-enabled products and services become more integrated and commonplace. The continuous influx of corporate products at a relentless pace only serves to underscore and perpetuate this tensioned adoption scenario.
“But there’s hope. Outsiders can bring in 2024 change through leapfrogging innovation, especially in areas or among groups that haven’t been part of this tech wave yet. We’ve seen before how this is the way to create new products, services, and experiences that quickly become the norm for everyone. That would be true disruption.”
The surge in GenAI is being propelled by unexpected and remarkable models. Predicting their next move is futile, as anticipating the next trick from GenAI models is an impossible feat. However, it’s easy to identify certain expectations.
Recently, these models have become more interconnected and adept at handling near real-time data, a trend that is expected to expand in 2024. The potential challenges of data pollution or malicious data injection may emerge, presenting a growing difficulty to counter. Simultaneously, the landscape for innovation may broaden.
The current status of GenAI models exacerbates these safety concerns. They operated as de facto black boxes that appear impenetrable and indecipherable. Stakeholders are pinning hopes on challenging this paradigm through the development of Explainable AI (XAI).
XAI aims to make AI and machine learning decision-making processes comprehensible, empowering users to understand, trust, and manage these technologies effectively. However, the feasibility and mitigation of these challenges within the current realm of AI technologies remain open questions.
“Generative AI will allow organizations to design cars by simply speaking to a large language model or create cities from scratch using new techniques and design principles,” Pette said.
The AECO industry is shaping the future with generative AI as its guide. Numerous startups and customers in AECO and manufacturing are dedicated to creating solutions across diverse use cases. These vary from design optimization and market intelligence to construction management and physics prediction. AI will accelerate a manufacturing evolution that promises increased efficiency, reduced waste, and entirely new approaches to production and sustainability.
“Developers and enterprises are focusing in particular on point cloud data analysis, which uses lidar to generate representations of built and natural environments with precise details. This could lead to high-fidelity insights and analysis through generative AI-accelerated workflows.”
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