#CloudMinds tackle the future of cognitive in Las Vegas huddle

The #CloudMinds kicked off huddle season in Las Vegas during IBM InterConnect with a wide-ranging discussion about the cloud and future of cognitive computing.

Angel Diaz, IBM VP of Developer Technology and Advocacy, and Willie Tejada, IBM Chief Developer Advocate, hosted the event, which included 14 #CloudMinds.

The conversation kicked off with a question: Why do some IT organization leaders still view the cloud as less secure than a private corporate data center when the opposite is almost always true? It was posited that it may be explained by the Dunning-Kruger effect, the phenomenon whereby low-performing individuals overestimate their abilities.

From there, the conversation turned to cognitive, which is where it stayed for the remainder of the evening.

Several major themes emerged from the huddle, which we will focus on through public-facing articles and discussions in the coming weeks and month. Each of these takeaways sparked a series of questions for further exploration.

A diversity among technologists, backgrounds, regions, specialties, industries and ideas is needed to prevent cognitive biases.

  • What can technical leaders do to maintain diversity and avoid biases when creating cognitive solutions?
  • Is there room for and/or need for a foundation around cognitive development?
  • What aspects of cognitive computing are ideal for open sourcing?

Cognitive and artificial intelligence (AI) are only as useful as the solutions we create with them. Technologists have an opportunity to accelerate and grow the number of people who are using cognitive tools and applying it to real-world problems. Still, more needs to be done to put these tools in the right developers’ hands and help them understand its abilities and limitations.

  • How can we advance no code/low code to the point where we’re easing innovation at the enterprise level?
  • How can we bridge the gap between the technical and non-technical worlds?
  • What are some of the aspects of cognitive that can be democratized in a way that

We cannot continue to overvalue the code contributors and technologists behind these capabilities while undervaluing the end consumer.

  • How can we make it easier for users to understand cognitive, what it means to them, and how it affects (and will affect) the technology they use every day?
  • How can we make the user a more integral part of the feedback loop?

The coming months and years will see a shift at the enterprise level from an emphasis on digital transformation to an emphasis on cognitive transformation, which encompasses AI, machine learning and deep learning. It is our responsibility to usher those enterprise clients.

  • How do we help our clients and business partners understand that this transformation is eased through a cloud native approach?

There’s a seismic shift coming to the role of the developer. The very definition of development is changing. It is our responsibility to help developers and the world address this change.

  • What can platform providers do to ensure that the tools developers are using are pervasive, easy to use and effective?
  • How can we continue to encourage more participation in open source communities and empower our developers with the right data?

IT professionals are focused on the wrong problems. Technologists tend to look past grand societal problems to focus on fast solutions to smaller problems.

  • How do we bridge the gap between what we think we need to solve vs. what we should actually be solving?
  • What are some of the bigger problems we should be addressing with cognitive?
  • Do companies that use cognitive tools have a responsibility to tackle these larger problems?

As we continue to deliver cognitive solutions and build cognitive technology, ethics will play a critical role in fighting “fake cognitive” and self-serving or select-serving cognitive.

  • How do we validate cognitive tools? Can we validate them?

Cognitive cannot and will not exist without trust. Humans will not trust cognitive unless we can show that our cognitive solutions understand them.

  • What is a legitimate and achievable goal for cognitive human understanding?
  • What is the macro moonshot for cognitive?

As we continue throughout the year, we’ll be exploring many of these themes and questions through a series of articles, podcasts, videos and more.

For now, we’d love to get your thoughts on some of these. Please let us know what you think about some of these questions and where you see the future of cognitive taking us.