What Jobs are at Risk due to Generative AI?

🗞️ The Tech Issue | September 25, 2023

☕️ Greetings AI enthusiasts! It's Monday, September 25th. Welcome back to my daily dive into the AI landscape. We'll navigate the latest updates, trends, and insights from the AI world. Let's begin!

♨️  Indeed's AI at Work research paints a sobering picture of GenAI's potential to disrupt the job market. While it suggests that no job is entirely immune to GenAI-driven changes, full job replacement remains unlikely, particularly in roles demanding hands-on skills or emotional intelligence. However, almost 20% of current job roles could be highly susceptible to GenAI interventions, raising concerns about job loss and labor market volatility. GenAI's self-assessment corroborates this, claiming excellence in only a small fraction of job-related skills. The findings serve as a cautionary note on the risks of relying too heavily on automation and AI.

🗞️ Today’s Highlights:

  • LATEST NEWS & TRENDS — Learning to Use a New Tool: The Impact of Generative AI on Work, Now and in the Future

  • INDUSTRY | FUNCTION — Where Should Manufacturers Start with Generative AI?

  • RESOURCES — Generative AI on AWS: Everything You Need To Know

  • WORK — The urgency of understanding – generative AI and the new workforce

  • AI TOOLS — Inari: Your intelligent AI copilot for business

  • CHARTS — How People Can Create—and Destroy—Value with Generative AI

🗞️ LATEST NEWS & TRENDS

1️⃣ GenAI signifies a pivotal shift in AI's trajectory, integral to the Fourth Industrial Revolution. This surge in adoption stems from both technological maturity and a conducive environment. The technology is poised to expedite changes in the labor market, specifically automating low-value tasks. However, it's not spelling doom for creativity. Creative sectors may leverage GenAI for enhanced productivity. Moreover, despite GenAI's capabilities, humans are expected to retain ethical oversight and responsibility for its outputs in the foreseeable timeline.

Applicability of GenAI Automation (diagram below)

2️⃣ As AI technologies proliferate, the associated risks, including reputational harm and regulatory penalties, escalate. Companies are increasingly adopting responsible AI frameworks to mitigate these challenges. A report by MIT Sloan and Boston Consulting Group underlines the pitfalls of using third-party AI tools, which account for 55% of AI failures. It recommends expanding responsible AI programs, rigorously evaluating third-party tools, preparing for tighter regulations, involving CEOs in AI ethics, and ramping up investments in responsible AI initiatives to avoid falling behind or exposing organizations to significant risks.

3️⃣ Artificial intelligence is rapidly infiltrating the architecture and design sectors, offering next-gen solutions in text and image generation. While AI tools like ChatGPT assist in textual aspects like project descriptions, other platforms like MidJourney and Dall-E offer hyper-specific visual inspirations. These tools are useful but come with pitfalls like bias and hallucinations. Currently, AI serves best in early design stages and marketing but its potential is exponential, extending to code review and sustainability analyses. Human-AI collaboration has already demonstrated innovative designs, including SmithGroup's Innovation Campus for Virginia Tech. A balanced approach is crucial in leveraging AI for meaningful architectural innovation.

4️⃣ LLM Generative AI is revolutionizing the sales landscape by aiding in content creation, customer insights, and sales forecasting. Powered by large volumes of text data, this technology can generate human-like text that has multiple applications in sales. From crafting compelling product descriptions to offering personalized customer interactions and accurate sales projections, LLM Generative AI provides a competitive edge. While it presents promising benefits, businesses should also be mindful of ethical considerations and data security to harness its full potential responsibly.

5️⃣ ChatGPT and other generative AI models create content through a diverse array of data collection methods, spanning from automatic internet searches to public information repositories. These tools offer capabilities like translation and code generation but also raise ethical and legal questions. Data comes from various sources, such as web scraping, public domain material, and synthetic data created by other AI models. They also tap into crowdsourced information and customer records, as long as privacy laws are respected. Platforms for user-generated content offer another goldmine of data, although permissions are crucial.

🗞️ INDUSTRY | FUNCTION

GenAI in the Manufacturing Industry

The ubiquity of AI is poised to rival that of the internet and electricity, with generative AI such as ChatGPT serving as popular interfaces for mainstream AI engagement. The technology holds significant promise for multiple sectors, including manufacturing. However, with its rise come pressing questions of governance and strategy, including data privacy and appropriate usage. As companies increasingly adopt generative AI tools, they must delineate company policies and strategies, addressing potential risks and setting guidelines for internal and external applications.

🗞️ RESOURCES

Generative AI technology can create content, facilitate personalization, assist in software development, and more. Business benefits span from improving customer experiences to optimizing internal processes. However, the talent pool for generative AI is currently limited, exacerbating a skills gap that may widen further. AWS provides various training options to bridge this gap. Industry adoption of generative AI is booming, with a predicted impact of nearly $7 trillion on global GDP over the next decade.

  1. Amazon CodeWhisperer – Getting Started: A free, hands-on course for developers new to CodeWhisperer.

  2. AWS Jam Journey – Build Using Amazon CodeWhisperer: A challenge-based course ideal for DevOps experts.

  3. Generative AI Foundations on AWS: In-depth training for experienced AI enthusiasts wanting to specialize.

  4. Generative AI with Large Language Models: A three-week deep dive led by industry leaders, aimed at data scientists.

  5. Generative AI for Executives: Video modules that break down generative AI for C-Suite leaders.

  6. Generative AI Innovation Center: A mentorship program connecting businesses with AWS strategy experts.

🗞️ WORK

The workplace is in flux, with Generation Z entering the scene, bringing unique challenges like financial insecurity and mental health issues. Traditional metrics are losing their edge in understanding this diversity. Generative AI offers a fresh lens, providing real-time, actionable insights into the workforce. It bridges the generational gap by identifying unique challenges and preferences across employee age groups. Modern employers, in embracing these dynamic tools, can foster a workplace that's not just efficient but also engaging and empowering for all generations.

🗞️ AI TOOLS

Inari: Your intelligent AI copilot for business

Listening: Listen to Academic Papers on the Go

BlogToPod: Turn Your Blog Into A Podcast In Minutes

TryChatter: Dead simple LLM iteration and testing

Artie: Artie Transfer is an open source data integration platform that enables real-time data replication between databases and data warehouses.

Disclaimer: 1) The tool descriptions may include messaging from each tool site. 2) Please thoroughly read the site details before using and/or acquiring any of the tools listed above.

🗞️ CHARTS

 👀 A groundbreaking study reveals a paradox in public perception of generative AI like GPT-4: While people are skeptical in areas where AI excels, such as creative ideation, they over-rely on it in tasks it's not yet proficient at, like business problem-solving. This mismatch affects performance, with people doing worse when trusting the AI's suggestions in its weaker domains. The findings underscore the importance of managerial intervention in guiding the proper utilization of this emerging technology for optimized outcomes.

Reference/Source: Boston Consulting Group (How People Can Create—and Destroy—Value with Generative AI)

Disclaimer: The audio-visual content is courtesy of the source provided above.

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I'm not a newsletter expert so you might find my approach a tad different. In my daily dives into the world of AI, I handpick the latest gems, initially to support the AI projects that I’m working on. Realizing that these snippets might resonate with others, I thought, "Why not share this with my community and fellow AI enthusiasts?" I truly want this newsletter to be valuable to you so if there's anything on your mind—praises, critiques, or just a hello—please drop me a note. You can hit reply or shoot me a message directly at my email address: [email protected].

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