👩‍💻 Filling Roles in an AI Team

DTP #44: How AI Features Can Change Team Dynamics

This week: 

  • AI Features in Communication Tools: Generative AI adoption impacting workplace dynamics. 

  • Key Roles in AI Projects: Challenges in scaling AI projects due to lacking skills and collaboration. 

  • From the Web: Google considers paywall for premium AI-generated content. 

  • Ethical AI: Senior experts warn of social instability due to powerful AI systems. 

💼 AI in Business 

How AI Features Can Change Team Dynamics 

Image generated by Midjourney

Harvard Business Review looks at how Generative AI has rapidly been adopted, impacting workplace culture and conversations. 

  • AI-powered features in communication tools like Zoom and Teams offer feedback and summarization capabilities. 

  • Tools like Read AI analyze meeting interactions, measuring engagement, sentiment, and airtime. 

  • While these tools offer productivity benefits, they also pose risks if people rely too heavily on them. 

  • Conversations about AI-enabled communication are often absent in organizations, leading to potential missteps. 

  • AI can influence who speaks and gets heard, what gets said and heard, when we speak and listen, where we speak and listen, and how we speak and listen. 

  • The impact of AI on conversations depends on power dynamics, how knowledge is sourced, and the approach to learning and adoption. 

  • Wise application of AI requires consideration of its impact on relationships, trust, and reflective thinking. 

🤝 Key AI Team Roles 

The complexity of AI projects and the need for rapid production necessitate identifying key AI roles. 

  • Organizations struggle to scale AI projects due to lacking skills, collaboration, tooling, and know-how. 

  • Gartner predicted that 50% of IT leaders will face challenges moving AI projects past proof of concept to production. 

  • To mitigate high failure rates, organizations must establish the right roles for AI success. 

  • Successful AI initiatives require collaboration among data scientists, data engineers, AI architects, and ML engineers. 

  • Collaboration with business domain experts and IT specialists is essential for successful AI initiatives. 

  • AI architects focus on transformational architecture efforts, orchestrating model deployment and management in production. 

  • ML engineers optimize ML solutions for performance and scalability, ensuring they meet technical and business requirements. 

  • The ML engineer role was projected to be the fastest growing in the AI/ML space, with an expected shift from one engineer per team to over 5. 

🌐 From the Web 

Google, considering charging for premium AI-generated content, explores paywall options. Traditional search remains free with ads. Recent AI controversies prompt reevaluation. No confirmed plans yet. 

The UK and US AI Safety Institutes collaborate on common testing methods and information sharing. They aim to address global AI safety concerns through joint efforts and international partnerships. 

WHO launches S.A.R.A.H., a gen-AI powered digital health promoter, aiding in understanding leading causes of death, providing up-to-date health information, and fostering interactive conversations. 

Google Cloud partners with Hugging Face, offering access to Vertex AI and infrastructure, streamlining AI model development for developers. 

Adobe research: 53% of Americans use Generative AI, foreseeing increased shopping, travel, and personal use. Embrace its potential but expect brands to improve customer experiences. Top interactions: chatbots, auto-generated replies, image generation. 

🕵️‍♀️ Ethical AI 

“AI firms must be held responsible for harm they cause” 

Senior experts, including pioneers of AI, warn of social instability due to powerful AI systems in a document ahead of a summit on AI safety. 

  • The proposal urges governments to allocate resources to safe and ethical AI development. 

  • Recommendations include independent auditing, licensing system, and liability for AI companies. 

  • Current AI capabilities pose risks such as amplifying social injustice and enabling criminal activities. 

  • The GPT-4 AI model demonstrates worrying capabilities, prompting concerns about autonomous systems. 

  • Policy suggestions include mandatory incident reporting and measures to prevent dangerous AI replication. 

  • Safety summit to address existential threats of AI, but no formal global regulatory body expected. 

  • Some experts argue against exaggerated fears of AI's existential threat, but caution is urged due to lack of safety measures and regulatory infrastructure. 

🤖 Prompt of the week 

Act as a programmer in Python. Please simplify this code while ensuring that it is easy to read: {Insert Code} 

See you next week!

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