Chethan: It’s a common concern among AI enthusiasts, and rightly so, given the abundance of accessible information these days. Organizations, operating within the confines of regulations and laws, often collect data they desire while attempting to avoid missing out on valuable insights. This predicament raises ethical questions regarding the appropriate utilization of such data. Allow me to illustrate this point with a brief example. In today’s social media-dominated era, whether you use Instagram or Facebook, you are exposed to targeted ads without even realizing it. These ads are specifically tailored to your preferences, subtly suggesting, “Hey! This is what might interest you.” How does this occur? We are aware that our phones capture our conversations, and various other methods of data collection are also employed. Behind the scenes, an AI system processes this data and presents relevant ads based on your location. I personally experienced this phenomenon. A few months ago, I underwent dental surgery. Before the procedure, I followed a specific route from my office to my house, picking up my wife along the way. During our commute, we often discussed dental clinics. To my surprise, I received a notification about a discounted offer from a dental clinic situated merely 50 meters away from my current location. It struck me that these suggestions were derived from my personal conversations with my wife. Consequently, I felt tempted to consider visiting the dental clinic due to the allure of discounted treatment. This situation emphasizes the ethical dilemma surrounding what is deemed right and wrong. However, it is crucial to recognize that regulations will undoubtedly play a crucial role in shaping the ethical use of data for AI purposes in the future. Governments and other regulatory bodies are actively engaged in overseeing and controlling these practices.
Ratnadeep: AI will be much much straight and tightened in the coming days. Looking at the possibilities that AI has, let’s talk about a few success stories and missteps. Could you share a cautionary tale from an organization that didn’t prepare for AI adequately?
Chethan: I would say there are several use cases, as I mentioned earlier. AI has the potential to be highly successful when well-defined. Currently, larger enterprises are leading the adoption of AI and data utilization within their processes. These organizations have vast amounts of data at their disposal, which they recognize as crucial for their future growth. We have collaborated with some of these enterprises, who have embraced the current AI trend. However, certain internal factors, such as hierarchical structures, hinder their progress in implementing AI solutions. As I mentioned before, a proper data-driven mindset and infrastructure are necessary to effectively define AI use cases. Unfortunately, many organizations are eager to jump on the AI bandwagon without considering the extensive process involved. Without discipline, structure, and the right infrastructure, successful implementation becomes challenging. Consequently, a significant portion (around 80-90%) of AI initiatives fail to reach the production stage due to these reasons. On the other hand, I also work with startups that prioritize efficiency over formal processes. Despite their unconventional approach, they have well-defined structures and unique use cases, which can have a substantial impact within their organizations. I have been involved with one such startup from its early bootstrap phase, and I consider myself a partner in their journey. They have made impressive strides in technology adoption and AI utilization, leading to significant growth within just a few years. I can provide a noteworthy case study in the fintech space where they use AI to expedite loan processes, resulting in faster and more accessible loan offerings. This use case has a tangible impact on people’s lives. Furthermore, these startups are also efficient in their internal operations, saving substantial time compared to traditional banking processes for loan applications. Through AI implementation, they streamline and expedite the loan process, benefiting both the organization and the customers. This is an excellent example of an impactful use case that enhances efficiency. In summary, there are various use cases for AI, with larger enterprises driving its adoption. However, internal factors can impede progress, necessitating a structured approach. Conversely, startups with well-defined structures and unique use cases can achieve remarkable results. One such case study in the fintech sector demonstrates how AI accelerates loan processing and positively affects customers’ lives.
Ratnadeep: I have a similar story about a health tech company we’re currently collaborating with. We began our partnership during their bootstrap phase, and they’re now on the verge of receiving substantial funding. Startups probably grasp certain concepts better than most enterprises. Now let’s talk about the future of AI. Do you have any surprising predictions about AI’s role in businesses? And, if an organization is reluctant about getting AI-ready, how would you convince them that they are missing out?
Chethan: I’m not certain how to accurately predict what AI will bring in the future. However, it’s likely that AI could assist us in improving prediction capabilities. It is important for us to accept the ongoing change that is happening. This transformation is unstoppable, and everyone should embrace it. One common misconception is the fear of AI taking away jobs, but in reality, it is ultimately dependent on people. AI can enhance efficiency and productivity, but individuals need to adapt and learn from new systems. That’s how progress should be approached. As for the future, widespread integration of AI may take some time, especially in everyday life. Currently, we observe real-use cases in robotics, such as Boston Dynamics’ robotic dog. Although technologies like Alexa represent advancements, complete integration of AI will require more time. Nevertheless, it is inevitable and we should prepare ourselves. Just like the impactful revolution brought about by WhatsApp, AI will shape our lives in unforeseen ways. We are currently in a data revolution era, where data is being shared and utilized in various ways. If ethical and beneficial solutions can be built with this data, it should be embraced. However, there will always be individuals who are reluctant to accept new developments. It is important to be proactive and adaptable in order to stay ahead. Organizations should ensure their data is ready and their infrastructure is in place before diving into AI initiatives. Being prepared for AI is a wise approach in today’s era. Over the next decade, we can expect to witness exciting advancements, provided there are adequate regulations to protect human rights and ensure ethical practices. Let’s move forward effectively and ethically, knowing that AI, like Thanos, is listening and stating, “I am inevitable.”
Ratnadeep: So, as we wrap up, could you share an AI-related book article or a resource that has profoundly impacted you? Also, why would you recommend it to our listeners? And additionally, how can our listeners turn what they learned from this podcast into actionable steps right away?
Chethan: I must admit, I wasn’t really a big fan of reading books until recently when I was recommended one by my mentor. The book is called “Human Compatible: Artificial Intelligence and the Problem of Control” by Stuart J. Russell. I haven’t read much of it yet, just a few videos, but it delves into the challenges of aligning AI systems with human values and the ethical implications involved. It’s quite fascinating, and I think people interested in bringing AI into their lives should look into Stuart J. Russell’s work. As AI becomes increasingly integrated into our daily lives, it’s important to consider how it aligns with our day-to-day activities, and this book addresses that topic. Before we wrap up, I’d like to mention that technology keeps evolving, from Information Technology to internet technology, and now it’s all about access to information and the internet combined with the power of AI. So, I encourage you to start exploring and embracing these advancements. If you find something you like, go with the flow and take a step forward. That’s my personal belief. As for assistants like you, I think they’ll play a significant role in this ever-changing landscape. Chethan, I agree with you on that point. It has been an enlightening conversation today, and your insights into AI readiness, digital transformation, and your experiences have given us a lot to ponder. For those listening, I hope this discussion has provided valuable insights on how to navigate the journey towards AI readiness, not just technologically but also in terms of mindset, culture, and ethics. As we continue to explore AI’s role in our businesses and lives, conversations like these equip us with understanding and curiosity to move forward. They remind us to stay aware, be prepared, and seize the opportunities that AI and digital transformation present.
Ratnadeep: A huge thank you to you Chethan, for taking the time to share your wisdom with us today. I know our listeners will find it as invaluable as I did. For our listeners, who would like to learn more about Chethan’s work at SyntacticAI, we’ll include links and resources in the episode notes(description). I highly encourage you to explore them. In the spirit of continuous learning and growth, I would like to end this episode with a challenge for all of us. Let’s take one key takeaway from our discussion today and put it into action within your organization. I’m Ratnadeep, Co-founder of TechVariable and it’s been a pleasure being your host today. Stay curious, keep innovating, and let’s shape the future of digital transformation together. Until next time on “Leader’s Perspective”. Thank You.
