Future of Artificial Intelligence and Machine Learning

About the Guest 

George has been in the EdTech industry for over 25 years working with software professionals, building turnkey software organizations and commercial software solutions.  For most of this time, George has worked for Follett running their K12 commercial platforms division.  This has allowed George to pursue his passion for driving culture and operational excellence, developing world-class teams, and creating award-winning software platforms. He has sat on several boards including the Alliance for Learning (A4L), and the Student Data Privacy Consortium (SDPC), spearheaded several acquisitions and built strong customer relationships across North America. 

Connect with George Gatsis

Key Takeaways 

• George, who has 40 years of industry experience, has witnessed a tremendous evolution from card-reading mainframes to desktop and then cloud.

• The rate of innovation has exponentially accelerated with the move to web-based applications, compounding transformation, and minimizing expenses on a daily basis.

• AI and machine learning are here to stay – a reality whose ramifications are still largely unknown but quickly coming into focus. The trickle-down effects for programmers and all other tech-related fields are enormous, complex, and unfolding.

• Remote work has its own set of requirements, but George believes in one form or another it will remain a standard option post-pandemic. He suggests two concrete measures that enlightened leaders will want to exercise: Trust and Metrics.

Quote 

“As we get into machine learning … things are changing really on a daily basis. So we need to invest in our people to push them to learn new things and get out of their comfort zones.”

Highlights From the Episode

Can you provide some perspective on software development and how it has evolved over the decades?

When George first started out, computing was done with cards and readers – light-years from where things went once the micro-computers and desktops emerged. Initially, the software was for floppy disk drives and in the “dark ages” of software development. Things moved much more slowly and were miles away from the internet of things. When development started to accelerate, standard procedures had to evolve to keep up (out of this came the “Agile Manifesto,” which quickly caught on as an industry game-changer). 

What about transformation within the product development space?

Around 2000, in the dot.com bubble timeframe, the internet displaced LAN and web-based development and languages became the norm, as opposed to the old client-server architectures. The space was suddenly unlimited – and the scrambling to redefine things like storage began. The costs came down dramatically and the landscape has been utterly transformed.

What were George and his team’s initial responses to the tidal wave of new web-based technologies at the turn of the millennium? 

Engineers are always looking at and talking about new technology. On the one hand, they want the newest and greatest, but on the other hand, they don’t want anything to change. These things are diametrically opposed. At its heart technology is about people and tools. As George got deeper into his career his technical expertise became secondary to managing team members and ensuring they had the process, techniques, and capabilities necessary to deploy new tools. It’s a daily challenge to get people out of their comfort zones, ready to adopt new technologies so that they don’t become outdated. Replacing obsolete technology and archaic legacy systems is essential to moving forward efficiently. 

What does George foresee in the coming decade – both innovations and threats?

We’re looking at the early days of machine learning and can expect equally stunning acceleration. People are looking at robotics and AI/ML but the theories around their applications are far from unified. That’s probably going to happen in the next six months, twelve months, or eighteen months. I think it’s going to explode. It will be interesting to see what this AI capability does to the programming industry itself. Machine learning will change the face of many professions/sectors. Blockchain is also an emerging factor of the sort redefining many traditional spheres and practices.

How has George managed to change circumstances and expectations?

George’s team was already very distributed, with only a fraction reporting to the office on any given day, over the past five+ years. Agile practices with simple, well-defined processes to establish metrics about productivity are key. It’s critical that the culture’s leadership incorporate a hybrid mentality, including trusting workers as well as instituting measures for accountability. It’s important, however, to measure the right things and ensure that teams hold themselves accountable. 

Is there any book, podcast, video, or other resources that you’d like to recommend?

• “Good to Great: Why Some Companies Make the Leap … and Others Don’t,” and anything else by the author, Jim Collins.
• “Leading Change,” by John P. Kotter

Shout-Outs

• Girish Seshagiri – Director, Board Of Directors at Ishpi Information Technologies, Inc.
• Kim Wheeler – Director of Development Projects at Follett School Solutions
• Tim Rogers – VP of Technology at Wonderlic