In this Leading with Data Episode, we have with us Dr. Kirk Borne, a top global influencer, data scientist, astrophysicist, and TEDx speaker. He is a thought leader in big data, AI, machine learning, and more, and is an elected Fellow of the American Astronomical Society. We’ll explore his views on AI evolution, technology hype cycles, edge computing, and the challenges in adopting AI.
You can listen to this episode of Leading with Data on popular platforms like Spotify, Google Podcasts, and Apple. Pick your favorite to enjoy the insightful content!
Key Insights from our Conversation with Dr. Kirk Borne
- Generative AI is currently experiencing the downward slope of the hype cycle, indicating a phase of disillusionment following initial excitement.
- The cycles of technology hype are accelerating, with new technologies being adopted at an unprecedented pace.
- Edge Computing remains a critical area of focus, essential for real-time decision-making in IoT and other applications.
- Organizations adopting AI should focus on building the right data infrastructure and fostering a culture of experimentation.
- Generative AI has the potential to significantly improve customer service and healthcare but also poses risks in cybersecurity.
- AI professionals should prioritize lifelong learning and adaptability, focusing on foundational skills and problem-solving methodologies.
- Data storytelling and communication skills are invaluable for AI professionals to effectively convey insights and drive decision-making.
Let’s look into the details of our conversation with Dr. Kirk Borne:
How has the journey of AI evolution been for you in the last seven years?
Well, it’s been quite a journey. Seven years ago, the focus was on big data analytics and getting organizations data literate. AI was barely in the conversation. Now, it’s all about AI, especially generative AI, which is the hottest topic. I’ve observed a shift from organizations intensely diving into data analytics to now demanding AI solutions, only to realize they need the right data infrastructure in place. It’s a cycle of excitement followed by a realization that we need to get back to the basics of data.
What are your thoughts on the hype cycle of AI technologies?
The hype cycle is fascinating. It’s a pattern that repeats itself, regardless of the technology. We see a rapid uptick in excitement followed by a decline into the trough of disillusionment. Generative AI is currently on that downward slope. It’s like overindulging in your favorite dessert and then not wanting it anymore. We’ve seen this with various technologies, and now, with generative AI, we’re realizing that we need the right infrastructure and training to truly leverage its potential.
How do you see the cycles of technology hype evolving?
The cycles are definitely accelerating. What took decades for older technologies now takes days or hours for new ones like ChatGPT. The features of the hype cycle remain, but the pace is much faster. It’s a reflection of our societal and psychological tendencies to get excited about new things and then quickly become disillusioned if they don’t meet our immediate expectations.
Can you share insights on the importance of Edge Computing and its place in the hype cycle?
Edge Computing is crucial because it’s about taking action where data is collected, like in IoT devices or self-driving cars. It’s been at the peak of the hype cycle for years because it’s a long-term development. It’s where the future is, with applications needing to respond immediately, like in healthcare or cybersecurity. Edge AI is about making decisions at the point of data collection, and I believe it will continue to be a major focus area.
What does your Data Leadership Group offer?
The Data Leadership Group is a group of services I offer, including training, education, mentoring, strategic advising, keynote speaking, and social media influence. I help organizations build up competencies and skills, promote products and services, and provide insights from my 40 years of experience in data systems.
What common challenges do organizations face when adopting AI, and how should they approach it?
Organizations often jump on the AI bandwagon due to FOMO or without having the right data infrastructure. There’s also the fear among employees about AI taking over their jobs. It’s crucial to have a culture of experimentation, where you can fail fast to learn fast. Set up a sandbox for safe testing and understand that not everything will work perfectly. It’s about integrating AI into your existing mission, not making AI your mission.
What are some exciting and worrying applications of Generative AI?
On the positive side, customer service can greatly benefit from generative AI by handling FAQs and allowing human agents to tackle more complex issues. In healthcare, generative AI can help doctors quickly access the latest research for better diagnoses. On the worrying side, the use of generative AI for creating fake voices or identities, especially in cybersecurity, is a major concern.
What advice would you give to AI professionals early in their career?
Focus on learning the terminology and foundational skills like coding literacy and data storytelling. Embrace a mindset of lifelong learning and be adaptable to new technologies. It’s not just about the specific skills but also about the ways of thinking and problem-solving that will carry you through your career.
Summing-up
Dr. Kirk Borne’s insights on AI evolution, technology hype cycles, and the importance of edge computing have been invaluable. We’ve explored the potential and challenges of generative AI, and received practical advice for AI professionals.
For more engaging sessions on AI, data science, and GenAI, stay tuned with us on Leading with Data.
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