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AI / Operations / Tech Life

Bridging the AI-Human Divide: AI as Your Operations Teammate

AI is likely to be incorporated into society to work with people collaboratively and empower workers while driving improved productivity.
Oct 11th, 2023 6:08am by
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When it comes to discussions about Artificial Intelligence (AI), a shade of apprehension often colors the narrative — casting AI as the rival to people and their jobs. The problem with that assumption is that it ignores the historical relationship between people and technology. Throughout history, new technology has been adapted and adopted into society, whether it was the automobile, the integrated circuit or the cell phone.

Yes, technology brought change. But it often created new jobs in new fields and empowered people. AI is likely to be incorporated into society in a similar way — working with people collaboratively and empowering workers while driving improved productivity.

Unveiling Human-in-the-Loop AI

When viewed through the lens of collaboration rather than competition, AI should free people to do what they are uniquely good at — creative problem-solving, collaborating and using judgment to solve complex challenges. This “human-in-the-loop” approach to AI can alleviate people from daily-grind tasks that are time-consuming, repetitive, and often lead to burnout.

Envision a scenario where your AI teammate seamlessly integrates into your operational workflows, becoming a trusted assistant who handles time-consuming tasks. This teammate has a comprehensive understanding of your operations, understands the contextual importance of data and can deliver that data exactly when needed in the forms of metrics, graphs and recommended actions. Imagine an AI teammate that collects and sorts a massive amount of data, producing concise summaries for human analysis. Or AI that provides you with information that detects and contextualizes incidents.

The Imperative of Human Oversight

As potent as AI is in dissecting vast data sets, spotting patterns, and rendering contextual analysis, it’s still in its infancy. Its tendency to “hallucinate” or misinterpret data underscores the need for a robust human-in-the-loop (HITL) framework. This model fosters a symbiotic relationship where humans can verify AI outputs, providing a much-needed layer of validation and approval.

Real-World Examples of AI-Human Collaboration

There are plenty of examples already at play in the real world showcasing this type of strategic collaboration — where technology provides recommendations, but humans give the final stamp of approval.

Aviation: AI-Assisted Flying

The fact is that AI-like systems have been with us for some time. When you fly, a variety of systems work to keep you safe, to alert pilots of potential danger and even to keep the plane steady on auto-pilot. The thing is, you still have a pilot. Even with all of the automation on an airplane, you keep a human in the loop to make important decisions and ultimately land the plane.

Just as you wouldn’t remove a pilot from a cockpit, you wouldn’t remove human beings from tasks where judgment and decision-making are critical. The truth is, AI is fabulous at tasks like analyzing large amounts of data, finding patterns and providing contextual analyses; working alongside the unique expertise of humans will be the best partnership for modern ops teams.

Chess: Computer-Assisted Humans Make the Best Chess Players

The narrative of chess epitomizes the potential of human-AI collaboration. The advent of Advanced Chess programs didn’t overshadow human prowess; instead, it ignited a collaborative spark. This synergy shattered previous records, with humans leveraging strategic acumen and computers lending their computational might. Similarly, integrating AI into operational realms fosters a conducive environment for nuanced decision-making, driven by a blend of human expertise and AI analytics.

Just like in chess or aviation, bringing AI into operations helps teams make better decisions.

  • Data Integration: AI facilitates the transformation of disparate data into structured, actionable insights, setting the stage for informed human analysis. By tailoring data contextually, AI ensures a relevant, precise information flow to operations teams.
  • Automated Analysis and Understanding: Here, AI dives deep into integrated data, unveiling patterns and insights while humans steer the analytical direction, ensuring alignment with operational objectives.
  • Discoverability and Recommendations: AI explores the myriad of possibilities, presenting a platter of potential solutions. The ensuing recommendations are crafted considering the operational context, aiding the human in navigating the optimal course of action.
  • Augmented Machine Analysis: AI furnishes granular analytics, supporting the human in deciphering complex scenarios, thereby fast-tracking problem resolution.

AI As Your Operations Teammate

AI excels at presenting pertinent information precisely when it’s needed, offering insightful suggestions, and conducting comprehensive analyses of vast datasets. For an operations team, AI can become an invaluable, complimentary teammate. Rather than replace IT team members, AI functions as a valuable asset, helping team members be more productive and allowing them to focus on more strategic, high-value work.

Join us at KubeCon + CloudNativeCon North America this Nov. 6 – 9 in Chicago for more on Kubernetes and the cloud native ecosystem. 

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TNS owner Insight Partners is an investor in: Pragma, Real.
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