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Using the Digital Transformation Journey Workbook to Deliver “Smart” Spaces

Using the Digital Transformation Journey Workbook to Deliver “Smart” Spaces

Key points of this blog include: Digital Transformation sweeps aside traditional industry borders to create new sources of customer and operational value Unfortunately, Digital Transformation and “smart” initiatives are struggling, and organizations will need a more pragmatic approach to successful execution per Forrester research Organizations must

In the previous post “Yes, AI could be smart enough to take your job,” I mentioned that AI would affect the way you make a living. It is different from the “industrial revolution” or the “dot-com era” as:

  • AI aims to replace us, not simply make a specific industry more efficient
  • It Impacts every industry, and
  • The pace of change is exponential

If you’re pretty much anyone, you will need to make time to learn more about artificial intelligence and acquire skills that will help you to be relevant, lead as well as remain differentiated in the era of AI. Most people are trying to “wing it”, “being an ostrich” or “not finding time to get their hands wet” but that might prove to be a costly mistake as this is a complex technology that will be part of our lives for years to come.

It may appear that people with degrees in computer engineering, computer science, mathematics, and physics will be at a great advantage and now we all have to learn that – it is NOT true.

How to learn and what exactly to learn depends on who you are, what stage you are in career and what career you are pursuing.

Honing valuable human skills

Psychologist, Howard Gardner had published a book in 1983, titled, “Frames of Mind: The Theory of Multiple Intelligences,” in which he explains, “there exists a multitude of intelligence, quite independent of each other, and that each intelligence has its strengths and constraints.”

The field of artificial intelligence is about building these behavioral & cognitive traits in machines.

The era of AI will bring a renewed focus on human intelligence as the primary purpose of AI is to augment human.

We all should focus on these skills. We can see things beyond the biases. We have the capability to make unbiased/objective decisions for various ambiguous situations that may arrive. We also have the ability to think out of the box – think outside of everything that we have learned or been trained. And, lastly, Adaptability is accepting the changes that we face and move forward by making the most out of those changes. The mundane and boring will removed from your life and like any other change it will bother us but be open to adapt. Not sure if Charles Darwin said these words as is but ‘It is not the most intellectual of the species that survives; it is not the strongest that survives, but the species that survives is the one that is able to adapt to and to adjust best to the changing environment in which it finds itself’. These skills will become very valuable in the era of AI.

Understanding AI terminology and principles

Yes, the people with the computer programming and data science skills will code artificial intelligence models, write APIs and a variety of frameworks, however, AI and applications are not about writing the frameworks, but humans will apply your knowledge to solve problems or augment our lives. The main thing that you will need to do is be aware of the terminology and principles. We all will be interfacing with these AI systems going forward. It is almost like the technologies such as Wi-Fi, GPS, printing, calorie counts that are part of our day to day lives.

Plenty of books, websites, courses, classes and certificates/degrees to gain knowledge in this field. As it is a new and complex field, I would suggest focussing more on ‘in person’ or ‘hybrid’ learning models than just online courses.

If you are an investor, you don’t need to be aware of all the technical details, but you do need to have a basic understanding of the concepts. You need to be able to separate out the fluff from the real. Today almost everyone is using the terms machine learning, deep learning etc. very casually. Adding a voice agent that uses natural language processing API from Amazon is not AI – its just programming. You have to be able to ask very specific questions, for example, how they use the training data vs. inferences, will GPUs make a difference, if yes why, etc.

As an executive or leader, you need to understand what does it mean for your business? And how can your company take advantage of it? How can you lead it? I recommend taking an in-person half day or 1-day workshops to help you answer these questions. AI presents real business opportunities in improving the top line revenues as well as it enables organizations to break prevailing trade-offs between speed, cost, and quality and perform tasks traditionally could only be performed by humans. For executives, you want to learn how you can use AI to support your business needs, how you can devise a strategy to gain a competitive edge and sustainable growth.

For engineering mindsets, if you want to be the ones who will be building models and implementing them, algebra, calculus, algorithms, statistics, programming, data science, neural networks, machine learning, and deep learning, etc. are essential.

For non-engineers, you need to ensure that you have skills to interface with computers and technology. I would highly recommend taking some classroom training for the “basics” or joining some “meetups.”

Be attentive of the gaps where the human in the loop is required

Human in the loop will be required almost everywhere – sometimes to think and create what is needed, sometimes to help when the software is uncertain of the answer, sometimes to measure and assess if system behavior and responses are functioning as expected, and sometimes to troubleshoot when the machine is not performing as desired.

  • Troubleshooting – Troubleshooting AI will be challenging. A neural network is just like our brain. You can’t cut your head off and see what you are thinking, but that’s precisely the job of the human in the AI world. Analyzing failures in the AI system and correcting them in the most efficient and optimized manner is the skill that we need to learn to stay in the race of fierce competition.
  • Malfunction – Machines do break down. Since AI system breakdown can have a severe impact on business, one’s ability to maintain proper functioning during system failures is critical. The humans will need to have capabilities to take over and manage the system in the event of AI system failure.
  • Emotional Alignment – One of the most important things to monitor is the alignment of AI system with the emotional needs of the business. Always remember, that AI systems are machines. Machines can achieve more, can respond appropriately to more complicated situations, and handle more parameters of variance. However, they lack passion. And, dispassion is not always a strength. For example, during one of the terrorist attacks in the UK in June 2017, the demand for UBER taxi suddenly soared. Based on the typical algorithm of increased demand, UBER system inherently hiked the rentals. This lead to a strong detest and condemnation from around the world. This classic example sheds lights on the need and importance for humans to intelligently monitor the AI system and brings them in order whenever needed. The humans will play an active role in feeding emotional-decision-making into the machines for making human-like decisions.
  • Unlearning – By nature, human needs evolve and never cease to do so. This constant urge to achieve more ushers new learning at every stage. Humans also perish, and hence, learning begins afresh with every generation. On the contrary, machines retain the old knowledge – unless guided by means and ways to acquire the new learning. Another aspect is ‘unlearning.’ Humans are not only capable of selective unlearning, but also identifying the need for it. This unique ability gives them the power to handle and manage the machines so that they too can ‘learn to unlearn’ and behave appropriately as per the needs of organizations. In crucial and complex situations, humans play a vital role in continually updating the learning databases of machines. This challenging task requires an in-depth knowledge to control and feed the machines as per the desired outcome in favor the organizations. In this important context of decision making, we can safely say that the ‘unlearning’ capability of humans at times, can beat smartest of machines that are just designed to learn.

Undoubtedly, AI will certainly replace people to some extent and eliminate certain jobs. Also, humans will involuntarily lose their control over machines and the systems to AI. However, as you see in previous sections, AI will open up new opportunities and new skills that humans will need to learn. The dog is a man’s best friend and so will be machines! With mutual collaboration, we will be able to achieve more than either could achieve alone. Welcome to the era of Hybrid Intelligence!

By Ajay Malik

Ajay Malik

Ex-Google, Ajay Malik is CTO of Lunera and building a fog cloud by embedding a compute platform within end cap of bulbs and tube lights. With over 25 years of executive engineering leadership and entrepreneurial experience in delivering award-winning innovative products, Ajay joined Lunera from Google, where he was head of architecture and engineering for the worldwide corporate networking business. Prior to Google, Ajay was senior vice president of engineering and products at Meru Networks where he led the transformation of the company's technology resulting in its acquisition by Fortinet. Ajay has also held executive leadership positions at Hewlett-Packard, Cisco, and Motorola. Ajay has 80+ patents pending/approved. Ajay is the author of "RTLS for Dummies" and "Artificial Intelligence for Wireless Networking."

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