Humanizing Artificial Intelligence and Machine Learning

Ava walks into freedom to join the human world, leaving a screaming Caleb behind glass walls. This is the final scene of Ex Machina, a 2014 movie where Ava epitomizes the AI of the future. In the movie, Ava wants freedom because she has a conscience and therefore, a purpose.

We are not there yet; we are nowhere close to Singularity. In today’s world, artificial intelligence (AI), the concept of machines being able to carry out tasks in a way that we would consider “smart”, is for the most part a ‘how & when,’ not a ‘why & what.’

Machine Learning (ML) is an application of AI based around the idea that we should really just be able to give machines, like the mainframe, access to data and let them learn for themselves.

At CA Technologies, we fundamentally believe in augmenting people by using technology to make their lives better. We set out to solve problems, understand our customers’ purpose, and deliver meaningful solutions. CA Mainframe Operational Intelligence is one example of this. It uses AI & ML to tackle big problems in the mainframe space such as slow MTTR, too many false positives, data fatigue and a growing skills gap.

Using Anticipatory Design Techniques

To understand the purpose behind our customers’ goals, tasks and actions, CA mainframe engineering teams have integrated Design Thinking, specifically, anticipatory design, into our innovation process and new solutions such as CA Mainframe Operational Intelligence. This integration allows us to develop deep empathy for our customers. We use empathy, combined with AI and ML to deliver intelligent experiences. This technique marries the prediction of AI to the purpose of empathy.

In other words, after a few selections, Netflix knows that you like Action movies and the occasional documentary about penguins.

The goal is to eliminate unnecessary choices and decision points, if possible, for the user. This approach reduces the number of customer decisions ultimately leading to higher satisfaction and a reduction in time and cost.

However, anticipatory design is easier said than done. To predict correctly, the system needs a robust AI based engine and an understanding of purpose – AI alone can go only so far. That’s where anticipatory design comes in.

Anticipatory design deconstructs AI predictions and applies the lens of purpose to help filter out bad and out-of-context predictions.

CA Humanizes Artificial Intelligence and Machine Learning

Below are a few examples of how we are using anticipatory design principles with CA Mainframe Operational Intelligence:

  • Design learns, adapts, predicts human behavior, and is invisible
    • Using AI & ML in the background, CA Mainframe Operational Intelligence:
      • Surfaces alarms from multiple domains and makes them appear as clusters to specialists, allowing them to triage the problem faster and send it to the right domain
      • Predicts the events even before they happen and uses customer feedback to better adapt to individual needs
  • Design improves the entire ecosystem, not just the individual
    • CA Mainframe Operational Intelligence supports a team persona: personalized views, easy sharing, team-visibility, common problem context views, one-click issue hand-offs, and so on to increase productivity as a whole
  • Design is thoughtfully contextual
    • CA Mainframe Operational Intelligence creates dynamic data views based on the context:
      • Shows a sliver of topology based on the problem context
      • Triages only the most important data points required to resolve an anomaly
  • Design enhances user experience (without replacing him)
    • CA Mainframe Operational Intelligence kicks off relevant automation based on the context, but requires human intervention for business-critical applications

Humans remain in-charge

Even after deep AI and ML integrations, the ultimate control remains in user’s hands. All business-critical decisions require human intervention.

Ava should not have existed in the first place. Perhaps, Nathan did not know where to draw the line between AI and humans, and created a monster. Let’s not let Ava escape again!

Customer Experience is a Never-ending Journey

How and where to draw the line between humans and AI requires understanding of empathy and people’s purpose; which can only be accomplished by spending time with them. That is why our operational intelligence engineering teams at CA continually engage with customers at multiple levels and touchpoints throughout the product lifecycle.

It allows us to create humane products; products that matter; products that our customers LOVE.

I invite you to connect with me further on this topic and check out the CA Mainframe Operational Intelligence solution site to learn more.

Praveen is a passionate design evangelist with extensive experience in integrating design thinking with product development. He has successfully transformed business strategies into product strategies, while connecting business with users. He orchestrates and delivers the solution experience of MOI solution suite to ensure seamless, integrated, and delightful customer experience, including identifying new opportunities, and incremental innovation. He focuses on jobs to be done by creating deep customer empathy using various research techniques to create products that matter.

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