AI and Workforce in 2024

🗞️ The Tech Issue | December 5, 2023

Author

Qamar Zia
December 05, 2023

☕️ Greetings, and welcome to my daily dive into the Generative AI landscape.

I’m evolving this newsletter to ensure you, as a valued reader, eagerly anticipate opening it daily for valuable insights that keep you updated on Generative AI. My goal is to streamline its content, making it a concise, under-five-minute read. For those interested in deeper dives, I’ll provide references for extended reading. Most of this content springs from my ongoing research and development projects at Invenew.com. For more of my articles, visit ReROAR.com.

Today’s issue covers the following:

  • AI and Workforce in 2024

  • How is Claude AI Different from ChatGPT

  • Is AI leading to a reproducibility crisis in science?

  • Meta and IBM form an AI Alliance, but to what end?

  • Empowering Autonomous Driving with Large Language Models: A Safety Perspective

🔔 Please forward this newsletter to your friends and team members and invite them to join. This will help me grow my reach. Thanks, Qamar.

♨️ AI AND WORKFORCE in 2024

Exploring the intersection of generative AI and the future of work, this analysis delves into insights from industry leaders at McKinsey & Company, Johnson Controls, and AWS. These insights reveal a transformative impact on workforce dynamics, efficiency, and skills development.

Key Insights:

  1. Enhancing Productivity: Generative AI significantly boosts workforce efficiency, influencing 60-70% of current tasks.

  2. AI in HR: Streamlining HR functions, particularly in information retrieval and employee interaction.

  3. Workforce Expectations: Increasing adoption of AI in operations, with a focus on aligning employee skills and expectations.

  4. Democratizing Technology: AWS's approach emphasizes inclusive, multidisciplinary AI training and adoption.

  5. Cultural Shifts: AI represents a cultural change in workplaces, necessitating a human-centric, ethical approach.

  6. Future Outlook: Emphasizing skills-based talent, work evolution, and adapting to technological and cultural shifts.

The integration of generative AI in the workforce underscores a paradigm shift, requiring businesses to adapt strategically and foster continuous learning and innovation.

📈 TRENDS

Generative AI (GenAI) in 2023 experienced remarkable growth in enterprises, impacting various industries and governments. Predictions for 2024 include strategic integration, employee-driven adoption, open-source models, and specialized risk management.

Key Points:

  1. Rapid Integration into Enterprises: In 2023, GenAI became a core component in business operations across multiple sectors, enhancing productivity and innovation.

  2. Diverse Industry Applications: GenAI's adaptability led to its widespread use in industries like finance, healthcare, and creative domains, showcasing its transformative capabilities.

  3. Government Adoption: States like California began employing GenAI in public administration, marking a significant step in public service enhancement.

  4. Biopharma Industry Challenges: The biopharma sector faced unique hurdles in GenAI adoption due to regulatory compliance needs.

  5. Strategic Business Tool in 2024: GenAI is predicted to move from experimental use to being a strategic element in business operations.

  6. Rise of Employee-Driven and Shadow AI: Employees are expected to increasingly use personal AI tools for work, changing the landscape of AI adoption in enterprises.

  7. Open-Source Model Growth: There's a trend towards open-source GenAI models in 2024, indicating a shift from proprietary systems.

  8. Specific AI Risk Management: The development of specialized insurance policies for GenAI risks is anticipated.

  9. IDC's Predictions for 2024: IDC forecasts GenAI's role in co-developing digital products, sustained digital investment, integration in executive leadership, impact on digital-native businesses, and contribution to sustainability goals.

  10. Future Outlook: GenAI is evolving from an experimental technology to a key driver of business innovation, risk management, and competitive advantage, necessitating adaptation by organizations and individuals.

🗞️ IN THE NEWS

Meta and IBM have formed the AI Alliance, an industry body advocating "open innovation" and "open science" in AI. This collaboration aims to leverage existing partnerships, like the Partnership on AI, to create open AI resources for business and society. The AI Alliance will establish working groups and committees to focus on AI trust metrics, support AI training infrastructure, and set project standards. This move appears to counter the closed, proprietary AI vision of companies like Google, OpenAI, and Microsoft. Despite their open-source approach being criticized for potential risks, Meta and IBM emphasize collaboration for safer and more inclusive AI innovation. The AI Alliance, with diverse members including tech firms and academic institutions, faces challenges in aligning its broad spectrum of interests and defining concrete goals.

Europe is cautiously increasing generative AI investments, with a projected 115% rise to $2.8 billion, lagging behind North America's expected $6 billion. This restraint stems from Europe's focus on ethics and regulation, despite optimism in AI's business impact. France and Germany lead in spending and adoption, with substantial increases and implementation successes. However, only 6% of European companies have harnessed GenAI for tangible business value, highlighting the emphasis on managing ethical concerns and ensuring effective control over these systems.

🔦 INDUSTRY SPOTLIGHT

At Columbia University's forum, business, and research leaders discussed generative AI's potential in healthcare and finance. Emphasizing collaboration across disciplines, panelists explored AI's role in enhancing clinical workflows, improving patient care, and innovating financial processes, highlighting AI's augmentative rather than replacement role in decision-making.

  • AI is seen as augmenting, not replacing, human expertise.

  • Generative AI offers significant potential in healthcare and finance.

  • AI can streamline clinical tasks and improve patient care.

  • In finance, AI transforms data analysis and decision-making processes.

  • Effective integration into existing workflows is crucial.

  • The event emphasized interdisciplinary collaboration.

  • AI's future role includes enhancing human decision-making capacities.

🧰 GENERATIVE AI CHALLENGES

In late 2020, AI was proposed for diagnosing COVID-19 using chest X-rays, but flaws emerged. Studies, including one cited over 900 times, were challenged by researchers who found AI could diagnose COVID-19 from blank X-ray sections. This indicated AI was picking up irrelevant image differences, not clinical features. Numerous studies across fields showed similar errors, raising concerns about AI’s reliability in research. Efforts to fix these issues include proposed reporting standards and greater data transparency, but challenges in AI application and reproducibility persist, underscoring the need for careful, interdisciplinary approaches in AI research.

🏃 AI B2B INFLUENCERS

In 2024, generative AI is set to revolutionize B2B influencer marketing. A survey of 10 experts reveals AI's growing role in this domain. Key findings include 75% of B2B marketers investing in influencer marketing, with 93% planning increased usage in 2024. AI aids in identifying and selecting relevant influencers, with 60% of successful B2B brands using it for this purpose, and 66% for performance tracking. Experts predict AI's impact in areas like efficiency, audience segmentation, enhancing storytelling, augmenting human potential, creating AI personas, accelerating influencer research, and content creation. The emphasis is on balancing AI's analytical prowess with human creativity and personal narratives to maximize influencer marketing strategies.

🧰 TOOLS & APPS

In comparing AI chatbots, ChatGPT and Claude AI differ in training, architecture, and philosophy. Point by point, explored below are their distinctions and how they cater to varied preferences:

  • ChatGPT, launched in November 2022, gained global attention for its capabilities.

  • Claude AI, created by Anthropic, is emerging as a competitor to ChatGPT.

  • Both AI chatbots have similarities and differences in training methodologies, architecture, and design philosophy.

  • ChatGPT's training involves predicting the next word, sometimes resulting in inconsistent responses.

  • Claude AI uses Constitutional AI during training to prioritize helpfulness, harmlessness, and honesty in responses.

  • ChatGPT relies on the Transformer architecture with attention mechanisms.

  • Claude AI has custom modifications for safety and performance, aligning with Constitutional AI principles.

  • Both use reinforcement learning but with variations in approach.

  • ChatGPT focuses on versatility and safety, filtering problematic outputs after generation.

  • Claude AI emphasizes safety from the outset, making it distinct in its approach.

  • Free versions differ, with Claude having more recent training data for free users.

  • Paid users benefit from ChatGPT's later training cutoff and internet access.

  • The choice between Claude and ChatGPT depends on individual preferences and priorities.

  • Claude excels in data-related tasks and code generation, while ChatGPT is strong in research and academic writing.

  • Users have the flexibility to choose based on their specific needs and preferences.

📦 USE CASES

Matthew Rastovac, founder of Respell, began his journey in high school, automating tedious data entry tasks through code. Today, his company empowers non-technical employees to utilize generative AI for creating automated workflows. Respell recently raised $4.75 million in a seed round led by Craft Ventures. The platform stands out by catering to non-technical users, allowing them to build workflows simply by describing their needs. Unlike traditional drag-and-drop interfaces, Respell enables users to verbally describe workflows, which the software then constructs. Currently, the platform predominantly utilizes GPT-4. Craft Ventures recognizes Respell's potential in making AI accessible to a wider audience. Launched last year, Respell became generally available in August, and Rastovac plans cautious expansion based on financial performance.

👩‍💻👨‍💻 WORK & CAREERS

The economic analysis reveals that generative AI (GenAI) significantly differs from prior AI technologies, offering immense productivity boosts, particularly in creative roles. This new AI wave prompts leaders to reassess workflows and redefine job roles to harness GenAI's potential. GenAI impacts 44% of work hours across various industries, with the banking sector seeing up to 72% potential transformation. The technology not only automates routine tasks but also enhances creative and knowledge work, leading to substantial productivity gains and new avenues for corporate innovation. The implementation of GenAI necessitates a thorough job task analysis, identifying opportunities for automation and augmentation. This reshaping of work processes also demands a focus on talent development and reskilling strategies, ensuring that employees adapt to and excel in this new AI-influenced work environment. Responsible and compliant use of GenAI is crucial for businesses to remain competitive and innovative.

📚 RESKILLING

Singapore unveils National AI Strategy 2.0, aiming to triple its AI workforce by training locals and reskilling tech professionals from other sectors. Singapore's proactive approach in education and reskilling prepares it to embrace AI's potential, positioning the city-state as a competitive force in the global AI landscape.

🔬 RESEARCH

In the pursuit of commercializing Autonomous Driving (AD), addressing public trust and safety concerns is paramount. The limitations of deep neural networks in AD software, particularly in handling unforeseen scenarios, pose a significant challenge. This paper advocates for the incorporation of Large Language Models (LLMs) into AD systems. LLMs bring robust common-sense knowledge and reasoning abilities to the table, serving as intelligent decision-makers in planning. By integrating safety verifiers, this approach enhances AD performance and safety. While challenges persist, the integration of LLMs holds promise for reinforcing safety and performance in AD.

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