🎲 AI, composed interests?
AI data and trends for business leaders | AI systems series
AI’s progress comes with a crucial question: can AI develop its own interests, or are its goals forever intertwined with ours?
The initial societal reaction to AI is often to think about what existing work could be replaced by AI. Yet, most conversations I have with enterprises are around what *new* things AI can do for that organization that they weren't solving before.
Yes, we can get to information faster. But, we are still accomplishing the same thing with a piece of software.
What if AI does something for us? What if we ask the machine to complete our tasks?
Experts remain divided. Some, like Rodney Brooks in his book "The Embodied Mind," believe true AI will require a physical embodiment and interaction with the world, making the concept of "composed interests" a distant future.
Others, like Gary Marcus and Ernest Davis in their book "Rebooting AI," argue for a more cautious approach, emphasizing the need for robust safety mechanisms as AI capabilities continue to evolve.
Let’s try to better understand through facts.
📌 Fact 1: AI is not only a chat
AI's impact is undeniable, yet most companies are not taking advantage of its full potential. By 2024, a McKinsey Global Institute report estimates AI could contribute up to $5.3 trillion to the global economy1.
We see its influence everywhere, from facial recognition unlocking smartphones to autonomous vehicles navigating city streets.
Most companies are launching chat interfaces on top of their existing products “chats for everything”.
However, AI is venturing beyond basic automation and chats are just a UX paradigm shift. What used to be a GUI is now a chat, and you can interact with it.
This, thanks to machine learning algorithms that are now capable of generating art, composing music, and writing different kinds of creative content.
But raises the intriguing question of progress: are these merely advanced tools mimicking human creativity, or is there a spark of something more forming within these complex algorithms?
📌 Fact 2: AI is collaborative
There's a strong shift towards AI being seen as a collaborative tool rather than a replacement for human workers. Here's why AI is augmenting human capabilities instead of outright replacing them in most cases:
Synergy of strengths: Humans and AI have complementary strengths. AI excels at data analysis, pattern recognition, and repetitive tasks. Humans bring creativity, critical thinking, and social skills to the table. When combined, they achieve more than either could alone.
Focus on higher-level work: By automating repetitive tasks, AI frees up human employees to focus on more strategic and creative aspects of their jobs. This can lead to increased innovation and productivity.
Evolving job landscape: AI is creating new job opportunities in areas like AI development, data analysis, and human-AI collaboration. These require new skillsets but leverage human capabilities alongside AI.
This collaborative approach with AI is likely to be the dominant pattern. AI acts as a powerful tool that expands what organizations can do, rather than simply displacing workers.
📌 Fact 3: something is happening on the road ahead
Regardless of your stance on composed interests, there's no denying the need for responsible AI development. Open communication and collaboration between researchers, policymakers, and the public are crucial to ensure AI serves humanity's best interests.
That's where it's at, and the innovation is happening with AI Agents that will lead to full automation of entire jobs with agentic solutions.
Pros of agentic automation:
Efficiency and speed: AI agents can tirelessly work 24/7, performing tasks much faster than humans.
Accuracy and consistency: AI can follow defined protocols precisely, reducing errors and maintaining consistent quality.
Data-driven decisions: AI can analyze vast amounts of data to make optimal choices, potentially surpassing human judgment in specific areas.
Challenges and considerations:
Job displacement: A major concern is AI replacing human workers in various sectors. This necessitates workforce retraining and adaptation.
AI limitations: Current AI struggles with tasks requiring creativity, empathy, or complex social interactions.
Ethical considerations: Biases in training data can lead to discriminatory AI decisions. We need to ensure fairness and ethical implementation.
Do you have any specific examples of how AI is being used to augment human capabilities in the workplace? Let us know in the comments section.
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By 2024, a McKinsey Global Institute report estimates AI could contribute up to $5.3 trillion to the global economy: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier