In 2023, we witnessed AI making significant strides, transitioning from a novelty to a necessity. From GPT-4 to LLaMA-2 to Gemini, the evolution of AI has been truly groundbreaking. Despite its rapid integration, concerns surrounding ethics, data privacy, and the impact on the workforce continue to linger as AI becomes more pervasive.
Looking forward to 2024, we stand on the brink of another wave of AI reshaping industries and lifestyles. To gain insights into these upcoming trends, we have tapped into the collective knowledge of Appen’s executives and thought leaders to provide a glimpse of what lies ahead as AI advances in the coming year.
Transitioning from Generalists to Specialists: Embracing Provenance as the Theme of the Year
Current Large Language Models (LLMs) have showcased a diverse range of capabilities in natural language processing and comprehension, handling tasks like text generation, language understanding, and image creation. However, these capabilities are considered general skills that are applicable across various industries. In 2024, as AI evolves towards specialization, there will be a shift in demand from generalists to specialists.
The future will witness a focus on tracing back the expertise of highly skilled individuals with specialized knowledge in specific industry verticals that contribute to the development of these models. Their domain expertise will be crucial for creating reliable AI solutions for both consumers and enterprises. Furthermore, new revenue models, such as IP royalty streams, are likely to emerge, recognizing the human intelligence embedded in AI implementations. For instance, Appen VP of AI Strategy, Mike Shwe, anticipates that LLMs will leverage the expertise of IT specialists for tasks like data migration and software integration, which are high-impact and time-intensive.
The emphasis on human attribution aligns with the industry’s push towards controlled development of Artificial General Intelligence (AGI), advocating for human oversight in an increasingly automated landscape. This movement ensures that as machines enhance their computing and decision-making abilities, there remains human intervention to uphold ethical standards and prevent harm.
Evolution of Knowledge Workers into Freelance AI Agents
The job market is undergoing significant transformations, with the impact of AI on these changes being a topic of great interest. In 2023, we witnessed widespread disruptions and economic shifts across various sectors, prompting highly skilled workers to explore new career paths.
According to the A.Team Knowledge Worker Survey, 74% of knowledge workers expressed that the layoffs in the previous year made freelance work more appealing. In 2024, we can anticipate a growing number of knowledge workers opting for flexible roles as AI trainers, leveraging their expertise to train these systems effectively.
This shift signifies a broader change in the professional landscape, highlighting the importance of adaptability and redefining the concept of professional necessity. AI empowers knowledge workers to achieve financial stability through multiple income streams, and as more skilled professionals transition into AI specialists, the sophistication and power of AI systems are set to expand. This blend of expertise and adaptability will drive the advancement of AI technology, ushering in an era where AI solutions, guided by expert specialists, are tailored to address the most intricate industry requirements.
Embracing AI with Confidence: The Role of Risk Management Frameworks in Enterprises
Historically, large corporations, with more at stake, have been cautious about integrating AI into their operations. However, this mindset is poised to shift in the upcoming year, driven by initiatives like the NIST AI Risk Management Framework introduced in early 2023, paving the way for broader adoption in the private sector.
As AI regulation and normalization progress, organizations are becoming more comfortable with and knowledgeable about integrating AI technologies. Studies like the Microsoft & IDC report on AI integration in companies reveal a growing acceptance of AI:
- 71% of companies are currently leveraging AI.
- 92% of AI deployments are completed within 12 months.
- 52% identify the lack of skilled professionals as a major hurdle in scaling AI implementations.
With the incorporation of risk management frameworks encompassing risk assessment, documentation, and continuous monitoring into AI strategies, we anticipate a surge in AI innovation driven by trust and safety. This alignment between innovation and risk mitigation not only enhances the capabilities of AI but also solidifies its position as a catalyst for enterprise success.
Leading adopters of LLMs have already implemented comprehensive internal review processes for customer-facing LLM deployments before production. However, to address potential conflicts of interest, 2024 is expected to witness the rise of third-party evaluation and auditing practices for LLMs, akin to financial accounting and security reviews. Shwe predicts that government advisories and regulations will evolve in parallel with these third-party services.
Focus on Multimodal AI Systems: Pioneering a New Era of AI Capabilities
The optimism surrounding large language models has set the stage for a competitive race to develop multimodal AI systems. Both established tech giants and emerging startups are vying to lead the next wave of large language model AI innovation.
These sophisticated systems, equipped with multi-sensory capabilities, are on the verge of ushering in an era where AI can perceive the world akin to human experiences, encompassing sight, touch, and smell.
The implications of this technological leap are profound. Large Multimodal Models (LMMs) integrate diverse data types such as images, text, language, audio, and more, to address real-world challenges. Applications range from assisting the visually impaired community to revolutionizing industries like automotive and insurance:
- In the Automotive sector, technologies leveraging image, video, LIDAR, and language data are employed to detect driver fatigue and distraction.
- In Insurance, these technologies aid in understanding a plethora of claims documents alongside image and video data, streamlining processes like claims assessment.
As AI’s sensory capabilities expand, the need for human involvement becomes more critical. The synergy between human oversight and AI’s multi-sensory analysis ensures the relevance and applicability of these systems across diverse real-world scenarios.
The Future Unfolds: A Year of Transformation
Looking ahead to 2024, we anticipate pivotal transformations on the horizon. From knowledge workers reshaping their roles within the AI ecosystem to corporate boards bridging the AI skill gap, the upcoming year promises to be dynamic and revolutionary.
It is imperative to acknowledge that these evolutionary advancements hold value only when human involvement is prioritized. At Appen, we underscore the significance of human input and diverse perspectives in steering AI towards a safe and equitable future for all. This approach underscores the collaboration between human intellect and artificial intuition, highlighting the essential role of human ingenuity in guiding AI towards ethical and sustainable progress.
