ChatGPT and the like - an interesting era has begun!

My previous post with thoughts on "Artificial Dumbing" - the phrase totally coined by me - was pretty much in the words of ChatGPT! It is amazing how it expands blocks of ideas into such wonderfully articulated pieces of writing which largely resonate with what you think and want to communicate if you express yourself well enough to the tool. I hear a lot else is possible with Generative AI based tools already (check this out). And I am curious. Looking forward to try them all, at least the free ones.

What I have experienced through extensively using ChatGPT of late, is that the low hanging fruit of direct productivity improvements is something everyone must immediately tap into. It's primarily in terms of quick generation of specific content, including code, which would be as precise as the context and details provided by the requester. So, if you know what you want to achieve, just type your requirement as clearly as possible, basically whatever is in your mind and whatever you would tell yourself that you needed to do. And ChatGPT might give you a better output in a few seconds than what you might in a few hours. There are constraints on the type of input it takes and the type of output you can derive out of it. But then, you can be creative and push the boundaries to some extent. Also, the way the current ChatGPT works, you can use it to augment you, may be even do majority of the work for you, but there will be gaps and you have to fill those so that the output is complete, coherent and meaningful.

A powerful feature of ChatGPT is its conversational format, and working through multiple threads which behave like separate conversations. For example, if I am working on creating a report on a specific topic, with a many sub-topics, side-topics and nuances to deal with, I can first carry on a conversation with the tool like I would with an expert; exchange ideas, views and feedback, and through this process get to a point where, like a human, rather like a friend or colleague conversing with me, or perhaps even better than any of them in a way we wouldn't want to acknowledge, the tool actually understands my views and intentions which need to come in the report. Now with the framework already set, I would now ask the tool to give me the content as I desire, with the structure I want, with the nuances I want, with the messaging I intend and with the tone I desire. And even after that, if there are slight deviations, I can tell the tool to make necessary fixes, add or remove stuff I don't want, change the tone if I'd like, even change the person - pretend to be me or someone, and regenerate the content. I can make these tweaks multiple times, and even ask for many versions by regenerating responses, just for the heck of it sometimes. It won't take too many iterations to get what you need. It's not only a huge time saver, but also gives you the quality that you may not be able to deliver yourself in 100 times the time it took. And that is one aspect that both enthralls and worries me.

The reason it worries me, is that if tools like Generative AI become fully integrated into our lives, especially from our childhood, but also in later years, we will diminish, or not fully develop our abilities to imagine, create, express, articulate, write, draw and develop from scratch - something that is so unique to human minds and bodies, as we would have tools to do better job more effectively. The tools still have limitations, at least so far and for the near future, in being not capable of surpassing all human ability - what they call singularity - and are only capable of what they can copy / learn from, which is the entire body of human creation so far. Which means that there would still be value to things we can imagine or create beyond what anyone has ever done, and there are really no boundaries to that if history is anything to go by. But then, if we are out of practice with the basic level, aren't we generally dumbing down our faculties? How can we run for iron-man if we rarely jog or get into water or cycle?

Or am I looking at it all wrong? The time we save by using tools for mundane tasks can indeed be devoted to pursue goals of higher order. But the tools we are looking at have abilities beyond the mundane, and if we set boundaries to where they play a role, I think we'd be trying to suppress the impact of one of our greatest inventions. And something so great will always find its way around the stupidity / rigidity of humans, eventually.

There's another possibility. Human endeavor has always found newer areas and greater challenges. The invention of the wheel and everything that enabled us to move faster ever since, has possibly made us poor runners as a whole since we are less dependent on that skill for survival. Running has become a sport to compete in, with others interested, wanting, skilled and trained at running - it's become a form of entertainment that way. For many it's for fitness. But we certainly don't need to run from an angry tiger to save our lives or cover long distances on foot. The analogy is compelling but the key difference with AI is that we are playing with mental faculties now, and that's fairly recent. May be a few centuries later, we'll look back at this moment as a pivot in human civilization that totally transformed our lives, made us live longer, healthier and happier. Or may be we'll see this as the dark period that destroyed everything we stood for.

We must therefore develop this carefully, but definitely.

How do you think we must shape this? Can we, beyond a point? Where do we draw a line, to be safe? And should we?

I am tempted to ask ChatGPT for an answer...

Unveiling the Shadow Side of Corporate Decision-Making: The Era of "Artificial Dumbing"

In the age of rapid technological advancements and the pursuit of artificial intelligence, a contrasting phenomenon has emerged within the corporate world — one that can be described as "artificial dumbing" - a term I coined and which I think captures what's eating productivity of humans very deeply. This concept refers to deliberate non-intelligent actions taken by corporate executives that serve their personal interests, often at the expense of rational choices and genuine insights. From sales and strategy to delivery and beyond, artificial dumbing casts a shadow on the decision-making landscape. Let us delve deeper into this intriguing and concerning aspect of corporate behavior.

The Prevalence of Artificial Dumbing:
Artificial dumbing pervades various domains within corporate functions, where self-serving motivations can eclipse rational thinking. In sales, executives might resort to manipulative tactics and short-term gains, sacrificing long-term customer relationships. In presales, decisions may be driven by personal biases rather than objective evaluation, hindering the pursuit of optimal solutions. Even in strategy formulation, misguided ambitions and the desire for personal glory can lead to shortsighted plans detached from reality. This trend poses significant challenges to the pursuit of genuine progress and ethical business practices.

The Factors Behind Artificial Dumbing:
Several factors contribute to the propagation of artificial dumbing in corporate decision-making. The pressures of competition, quarterly targets, and the relentless pursuit of individual success create an environment that incentivizes short-term thinking and self-preservation. In addition, organizational structures and hierarchies sometimes prioritize individual achievements over collective wisdom, promoting a culture that rewards personal gain over the common good. Moreover, the abundance of information in today's interconnected world can lead to selective data interpretation, enabling executives to cherry-pick facts that align with their preconceived notions or personal interests.

Consequences and Implications:
The consequences of artificial dumbing can be far-reaching. It erodes trust within organizations, stifles innovation, and limits sustainable growth. Employees who witness such behavior may become disillusioned, and the overall corporate culture may suffer as a result. Moreover, the collective intelligence and potential of organizations remain untapped when decision-making is clouded by self-serving agendas. Ultimately, the negative repercussions extend beyond the corporate realm, impacting stakeholders, customers, and society at large.

Combatting Artificial Dumbing:
Addressing artificial dumbing requires a multi-faceted approach. Organizations should foster a culture of integrity, transparency, and collaboration, emphasizing the importance of long-term success over short-term gains. Encouraging diverse perspectives and empowering employees to challenge flawed decisions can help counteract personal biases. Furthermore, fostering a learning environment that values evidence-based decision-making and critical thinking can help dismantle the allure of artificial dumbing. Leaders must set the example by prioritizing ethical conduct and promoting a collective mindset focused on sustainable progress rather than self-interest.

Conclusion:
Artificial dumbing represents a concerning trend in corporate decision-making, where self-serving actions take precedence over intelligent choices and authentic insights. Recognizing and combating this phenomenon is vital for organizations to foster a culture of ethical decision-making, innovation, and long-term success. By challenging personal biases, fostering collaboration, and prioritizing collective intelligence, businesses can overcome the allure of artificial dumbing and embrace the transformative power of genuine intelligence in their pursuit of a better future.

Large Deals Closures - what are the IT services providers reporting?

This is the time for financial results in India. We had TCS share its Q4-FY23 results the day before yesterday. They sounded pretty decent to me in the first instance when I heard them, but then the market was quite brutal in declaring them disappointing. Infy came up with their own results yesterday, and although the results weren't that different in trends than TCS, the management sounded more nervous in communicating them and the market was more disappointed as expected.

However, one statistic that stood out for me was large deal closures. TCS had an all-time high volume of large deals signed, totaling to about $10 Bn in Q4 and $34.1 Bn in FY23. This baffles me coz if the market has that kind of momentum, why is the immediate sentiment so nervous? Infy on the other hand signed $2.1 Bn in Q4 and $9.8 Bn in FY23. I don't know whether that's good or bad in terms of performance, but what is interesting when you compare the two companies' large deal conversions is that TCS - which is 1.5 times Infy in its revenue - cracked 4.7 times TCV in large deals in Q4 and 3.5 times in FY23, when compared with Infy. How do you explain that?

Another statistic is Large Deal TCV as a multiple of total annual revenue. For TCS it is 1.17 while for Infy it is 0.52. Clearly there is something underlying that's not the same for the two companies.

I can think of two factors:

• Definition of "Large Deal": I checked a few places, including annual reports of both companies, but did not find anything mentioned on how the two companies define large deals. It would be great if companies clearly provide a definition, otherwise the large deal wins figure can be easily manipulated while reporting. One conventional way, among many others, to define a large deal is in terms of size - if the deal TCV is at least 10X the average TCV across all deals made by the company, then it could be called a large deal for that company. Given the size, scale and scope for TCS and Infy, I find it hard to believe that average deal size for TCS would be a couple of times higher than that of Infy. Another possibility is that TCS is winning many many more deals, albeit of similar large size.

A friend pointed out - and I think very correctly - that some companies count large contract renewals also as large deals closures. Is that the case with TCS? It seems so, coz otherwise these large deals will shoot the company's revenue next year when their year-1 value is earned. What about Infy? Neither of the two companies provide numbers of these large deals, which would have helped us understand these better. It must be intentional. I am keen to find out more on this.

• Advantage from size / scale or efficiency or offerings: If TCS is indeed able to crack bigger deals on an average, and also a huge number of larger than large deals than Infy - provided they both define large deals following the same underlying principles and benchmarks - then we can only try to explain why TCS is able to attract more and larger large deals. Size and scale of the company do increase its appetite for bigger deals, but the ability to deliver those depends on capabilities to deliver as committed, bring in efficiencies and offer value adds - which again the company can invest into and build better when at a certain scale - although that is not necessarily a given. Larger companies could be larger mess as well, but then they won't be large for long.

I checked the annual report of Accenture - a bigger rival to TCS - but it does not talk about large deals. Nor does Cap Gemini or Cognizant. Nor do some of the smaller Indian rivals I checked.

I can see why Large Deals matter in reflecting the health of client industries and the company itself. But if investors were to draw any useful comparison based on large deal conversion, they should be able to view them on the same scale. Otherwise there's room for manipulation and over-reporting just to manage optics. Similar used to be the case with reporting digital revenue, which was more distinguishing a decade back when digital was the buzzword.

So, what really are these Large Deals getting reported?

Being a Teacher

I owe most of what I am to all the wonderful teachers who have guided me along the way. So whenever I get the opportunity to wear a teacher's hat, I first reflect on 3 things - with all the teachers I have had the privilege of learning from, what worked, what didn't and what should have been.

Over the years I have taught different age groups ranging from secondary school kids aspiring for IIT JEE to business management post-grad students aspiring for great corporate careers to corporate employees to adults aspiring basic literacy and math skills. How you approach the learning process varies based on the audience, the setting and the context, and it's not just about the age.

I am not a professional teacher, nor an accomplished one. But as an amateur experimenter, I have learnt / experienced a few things about the role, and continue to explore the area with curiosity. And which I try to bring to the classroom whenever I get the opportunity. So, here is what I strive to achieve whenever I wear the exciting hat of a teacher. 

• Share and Facilitate, don't teach. A teacher doesn't know it all. A teacher is also a learner, except that he/she has a head start on the subject as compared to most of the students. Even that is not always a given, and depends on the students' profiles and unique experiences. A teacher's job therefore is to create a healthy environment for consumption and sharing of knowledge. And there could be many conventional and creative approaches to do that. To quickly set the framework at the outset without losing time or interest of students is an art. And to evolve the framework as the course unfolds, such that students still feel engaged and excited, requires finesse of higher order. A teacher therefore is an artist.

In my course on  IT project management, I have attempted to execute a peer learning model, where groups of students are expected to cover a lot of the course content, while I keep pitching in to provide insights from my experience and knowledge. I also selectively cover whole topics, but I'd limit that to those which I believe are deeply conceptual or where I have unique learnings or insights to share from my own experience.

So far, I must admit, in 3 attempts of teaching the same course - 2 of which were remote - I am still working on getting the model right. The recent attempt was in a physical classroom and the feedback was mixed - many students did not enjoy the presentations by other students, and the level of engagement on topics would depend too much on how it was delivered by presenters. The model was intended to facilitate learning from each other.  However, quite a few students were unhappy with the fact that there was less of 'teaching' and more of student presentations. Project management is something learnt from practice and experience. We all manage projects in some form in our personal and professional / academic life. I therefore thought rather than covering a lot of theory, learning through case studies and experience sharing would be more helpful. I also stressed on the fact that students so grown up should consume simple and basic concepts on their own, and class rooms should be for further discussions, so as to draw maximum value from the time we had. Not all students saw the merit of this, and perhaps there's a conditioned expectation to just watch / listen to a good performance by a prof. I definitely need to work on improving this model and also make it more engaging and entertaining. It is important to balance knowledge delivery with peer learning. While neither works beyond a point, one has to find the optimum mix of ingredients to get the taste that is irresistible.

In physical settings, there is an obvious unease in some of the participants in having to appear attentive constantly. While there is the human aspect of near impossibility of doing so, a prof looking on makes it worse. In the older times we let our minds wander elsewhere. Now there is the constant urge to retreat to gadgets, which is an unhealthy yet all pervading practice these days. And in remote settings, one can detach with little inhibition or guilt. This could be the reason why the previous 2 attempts - which were delivered and attended remotely - were probably taken more positively (based on limited student feedbacks collected). But I can't be sure, there could be other reasons.

• Don't set boundaries. In my own lectures on IT project management, I don't limit discussions to IT alone. I let my thoughts wander into any area as I speak, e.g. non-IT projects, student projects, cinema, relationships & dating, startups, psychology, careers, etc. etc. Analogies, rather than text books, help drive management concepts deeper. So I also encourage students to reach out to people in various industries and learn from real experiences, and think about how they can apply their learnings within the IT context. I can draw a picture of how it all looks like from my limited experience, but what if we could tap sources beyond the classroom and share, so as to enhance all our knowledge collectively!

I encourage thinking wild and random, with of course some relevance to the topic, and often try to drive this by example. I tap into my sense of humor to help make it fun, and I hope some of it is received in the right spirit.

• Interest is not a given. Especially for elective courses, which have been explicitly enrolled for by students, one assumes, or at least expects, the students to be interested in the subject. However, I have realized that it may not be the case for many students. It wasn't the case even when I was a student, and I do realize 'interest' was not the reason for enrolling for some of the courses that I did. Options, availability, ability to score, ease, grades expected, perception of the prof, demand for the course, what my friends were doing, etc. etc. all played a role. Therefore, when you are teaching a course, your primary effort should still be to generate and sustain interest for the course in minds of all the students. It's easier said than done, especially in the current education system which places greater responsibility of generating learning outcomes on the teacher. And with gadgets integrating more and more with our lives, and finding their way into classrooms, getting students' focused attention has become a very complex challenge.

• Respect. I make it a point to treat business management students as grown-ups, as professionals who must behave responsibly, act with dignity and follow professional etiquette. It is equally important that I conduct myself with the same standards, so that I evoke respect from students and also lead by example. I often feel equal to my students, may be because of not being a teacher by profession or conditioning. And that keeps me humble and grounded. I also make it a point to be fair, honest and transparent, which is part of my duty as a teacher.

I am sure I have a lot to learn and improve upon in my teaching ability and pedagogical approaches. I hope I get more opportunities and I can do complete justice to those with full commitment and dedication.

My goal is to equip my students for careers ahead. It is extremely fulfilling and enriching to be able to play a role, albeit small, in shaping stronger and more equipped leaders for tomorrow, and helping them enter the race with greater confidence, genuine skillsets and shorter learning curves.