For some time now, I've been deeply conscious of the impact of digital transformation in today's world. In an era where it is hailed as the key to organizational success, I have witnessed some organizations getting lost and confused on this transformative journey. Often, digital transformation is misinterpreted as merely implementing the latest tools and technologies. It could end up looking like a race not to be left behind, a haphazard move to showcase innovation, or an imprudent change to incorporate technology without considering the bigger picture.

The consequence of this "technology-first" mindset is a misalignment between the technology and the organization's overall vision. This can lead to wasteful investments, subpar user experiences, and ultimately, a failure to realize the true potential of digital transformation and derive the true value of the efforts.

Feeling concerned about this trend, I decided to address the issue in my blog through a dedicated column called #sensibletech. In these blog posts, I shared my perspective on the thoughtful implementation of technology, particularly within organizations. It felt like a good starting point until a friend made a thought-provoking suggestion:

"If you really care about it," she said, "as I believe that people don't read that much anymore, you should consider disseminating your thoughts through a medium that is widely consumed nowadays - video."

I stared at the wall in front of me as her words struck me deeply. As someone who finds comfort in writing, I had been hesitant to step into the world of audio-visual content creation. While I have occasionally spoken at seminars and videos, expressing my thoughts through written text has always been my go-to option. But my friend was right; to expand my reach and educate more people on this crucial topic, I needed to embrace a new medium.

Yet, doubts and questions flooded my mind. Was I technically and non-technically capable enough to host a podcast? Who is willing to be the guests? Did I enjoy being on camera enough to do it regularly? Could I handle the challenges that might arise in the future? Could I manage the entire process, from recording to editing, with my current capacity? Ultimately, will people watch it?

Fortunately, during my time at university, I encountered two kind souls who offered unwavering encouragement. Their advice was simple yet profound: "Start small," "Use the gear you have now and upgrade later," "I'll be your first guest if you need one," "Even if you don't have access to guests, you can do a monologue,", "Don't worry that much about whether the program will have viewers or not", and so on.

I realized that sometimes, all you need to find the courage is the support and push from people who believe in you and offer their unwavering support.

And so, here I am, presenting "Kenal Digital". With this program, my goal is to introduce a more thoughtful and strategic approach to digital transformation. I hope that the insights shared in this podcast lay the foundation for a careful and mindful digital transformation journey, where technology aligns harmoniously with the broader business strategy and even the broader system necessity. I believe that digital transformation is not a one-size-fits-all solution, but rather a tailored and customized expedition that enables companies to harness the true power of technology while staying true to their core values.

With gratitude and excitement, I present to you the first episode of "Kenal Digital." I hope you enjoy it.

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image source: CDD20 @ Pixabay

“AI is going to be one of the defining technologies of our time, and it's really important that we get it right." (Altman, 2023)

Although artificial intelligence (AI) had been around for more than half a century, I noticed that only recently, triggered by ChatGPT’s massive success, the general public started to pay close attention to it. AI has intercepted our daily life long before that (consider recommender systems in online marketplaces or social media platforms) but only in recent years that public conversations do not shy away from it. On my part, I have been very cautious to not give opinions regarding AI until I have enough knowledge. Now I think the conversation around this topic is necessary and timely and I am relatively ready. Therefore, I mustered up my courage to finally write about it.

(Disclaimer: While I have educated myself on the topic, I recognized the possibility that I am unconsciously biased or take less-than-necessary learning. After all, I am just an ordinary tech enthusiast with very limited knowledge so take this post with a grain of salt. I am ready to admit my mistakes on these thoughts if in the future they are proven wrong. I used ChatGPT as an example here not to undervalue thousands of awesome AI products, just as a representative of them.)

These days, Lex Fridman’s interview with Sam Altman (OpenAI CEO) occupied a large chunk of my brain. It is living in my mind rent-free and I have no problem with that. Unless Lex decided to ask me about the rent price, I would not dare to charge him. (LoL my unfunny joke is back!). On a serious note, the interview made me torn apart between wanting AI development to get full support (which sometimes means allowing the development to be highly experimental) and that it should be strictly regulated. I hope AI researchers/practitioners and regulators out there can find the perfect balance of leveraging the maximum possible benefits humanity can generate from AI while upholding the highest ethical principles and the responsibility of creating a better world without disadvantages that outweigh the advantages--including from the most vulnerable people’s perspectives. In a utopian society, I will end my post here because I have done my part of providing a recommendation as mentioned above. But we all know that this complex world of ours does not work that simply. So let me continue.

In recent years, the world is changing so fast right in front of our eyes and AI is one advancement the masses could not take lightly. AI systems have become much more powerful and relatively more reliable, which Sam narrated as “we don’t get mocked that much anymore”. AI used to be severely underestimated but now with recent advancements including GPT, many people even found it potentially “disturbs” mankind. Yes, while AI has created optimism and enthusiasm for many people, the other side of the population is scared and pessimistic about it. Sam himself is both excited and frightened--something that I appreciate because acknowledging both extremes of the benefits and risks is essential especially when the stake is this huge. He furthermore acknowledged that there will never be a completely unbiased version of GPT. What they can do is aim to make it as neutral as possible through RLHF (reinforcement learning from human feedback) and give more control to the people. For that reason, ChatGPT was deployed early to generate human feedback and also give the public more control so that it can be iteratively fine-tuned based on the collective inputs. Another thing I noticed is that GPT4 Technical Report (OpenAI, 2023) listed the possible risks like generating harmful advice or inaccurate information, and what the organization has done to mitigate them.

While definitely, the current AI has not yet “upheld the highest ethical principles and aligned with the best interests of humanity”, we should be a bit relieved that in this critical turning point of human history, people that (seemingly) strive to be balanced and cautious like Sam is in the driving seat. At least, OpenAI people are trying their best to get it right. I want to believe them.

Explainable AI (XAI)

To realize the full potential of AI, it’s important to prioritize alignment with ethical considerations and human values. The concept that I believe is useful to start this journey is explainability or interpretability:  the concept that a machine learning model and its output can be explained in a way that “makes sense” to a human being at an acceptable level (c3, n.d). Salierno (2023) described them as the ability to see inside what’s described as the “black box” of algorithmic decision-making while Miller (2019) defined them as how easily a human being can interpret and understand how the model arrived at a decision or prediction.

In simple words, XAI allows us to see the works between input and output. This is crucial because only through this transparency we can examine and evaluate AI models to ascertain what is influencing their decisions and identify any potential biases or ethics violations.

What is Next

After that, we shall evaluate the AI processes and models including their privacy and security aspects. The data collection and everything in the data life cycle should be transparently communicated to the data owner. The data behind the models should be governed properly mainly to ensure the quality of decisions made and the security aspects of the data. We should also consider how intellectual property would be negatively impacted by AI. Additionally, potential misuse of AI technologies such as deepfake should be mitigated by for example providing a mechanism to confirm the originality of a file (audio/video).

Other concerns that arose are regarding the accountability and regulatory aspects. A decision, even though generated by AI should be able to be held accountable. Therefore, who is accountable should be defined. In addition, regulatory development will probably always be outpaced by AI development. As a consequence, it is important to determine how can we ensure that AI is aligned with regulatory principles. We shall continuously monitor and evaluate AI processes and models, prioritizing the ones that have huge impacts on mankind. 

Closing

While I definitely cheer upon AI development, I also want it to be heavily regulated. At the minimum, I hope that AI models should uphold ethical principles and consider the best interests of humans and the broader systems. I know this balance is kind of difficult to achieve and I recognized all the hard work the AI people have done to achieve it. I am looking forward to a more robust, ethical, and reliable AI. I am optimistic about it.

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Image by rawpixel.com on Freepik

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References:

Altman, S. 2023. "Sam Altman: OpenAI CEO on GPT-4, ChatGPT, and the Future of AI" in Lex Fridman Podcast #367, <https://www.youtube.com/watch?v=L_Guz73e6fw&t=6324s>

c3.ai. n.d. Glossary. accessed at 10 May 2023, <https://c3.ai/glossary/machine-learning/explainability/#:~:text=Explainability%20(also%20referred%20to%20as,being%20at%20an%20acceptable%20level.>

Miller, T. 2017. Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence, Vol. 267, page 1038, https://doi.org/10.1016/j.artint.2018.07.007.

OpenAI. 2023. GPT-4 Technical Report. accessed on 10 May 2023, <https://cdn.openai.com/papers/gpt-4.pdf>

Salierno, D. 2023. Explainable AI pulls back the curtain on machine-made decisions. Internal Auditor Magazine February 2023, a publication of The Institute of Internal Auditors

image by rawpixel.com on Freepix

 "The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency." (Bill Gates)

(Hey, here I am with another (probably) hot take. You might think: doesn’t Nur Imroatun Sholihat advocate technology/automation implementation? Is she in her right mind when she said ‘don’t automate’? Please read till the end if you want, or at least the summary, okay? 😊)

Here’s the summary if you would prefer to not read the whole post: Use automation wisely, timely--be cognizant of what not to automate as much as what to automate, of when it is too early as much as it is too late.

     In my second term learning digital transformation at UNSW, I took a core course called Business Process Management (BPM). When I read the handbook, honestly, I was puzzled because a digital transformation should mostly be about digital, right? Why would the university’s School of Information Systems and Technology Management require the students to take such a course out of the blue?

      Now in week 8 of the course, I finally understood the reason why it’s made compulsory for the future digital transformation people. The realization still astonishes me today therefore I decided to write about it. Based on my newly-found understanding, at the heart of a digital transformation is the ‘transformation’, not the ‘digital’. The university wanted the students to, instead of jumping to automation directly, think more fundamentally when it comes to transforming the organization. The school taught the students to not consider automation as one solution for all. Automation is indeed one of the keys to the transformation door but let’s not be surprised that it isn’t the only one on the list (see the list below).

Redesign heuristics (Dumas et. al, 2018)

      Please don’t misunderstand me as I like automation as well (who wouldn’t though?). However, it concerned me that automation has grown as a solution that is easily misused. There is a common misperception that automation offers a magic mend to bad or broken processes. As much as I wanted it to be, let’s face it that it’s not Doraemon’s magic pocket (if it ever exists in real life) that solves all the problems instantly. It’s not a “plug-and-play” solution that could be straightforwardly implemented without careful adjustment and refinement.

      I know it’s uncomfortable to not directly think of automation when it’s already becoming one of the most-talked advancements organization could have. I also recognized how tempting shiny automation tools that promise exceptional optimization are. However, as I mentioned in my previous post, Luxury, “the ability to remain grounded amidst the sea of fancy buzzwords is a luxury. The ability to prioritize the fundamental things while having the serenity to not feel missed out is a luxury.”. Let’s have this uncomfortable discussion about the necessity and prioritization of automation.

      First, recognize that to fix a process to be in the best working order, automation isn't necessarily the most favorable answer. For example, does the process uniformly run or it has several unnecessary variations? If it has many variations, process standardization might provide more advantages than automation. Also, ask questions such as: is it better to be handled by machines or humans? Do the benefits of automation outweigh the costs? With our current capabilities and condition, when is the right time to automate? After that “pause and think” moment, we hopefully could gain a good working order, knowledge of which process to be automated, also investment and timing justifications.

     Second, as every organization operates with going concern assumption, act as a player in a long game. Not all automation initiatives should be implemented in a hurried manner--in other words: prioritize. Automation is known as resource-intensive activity therefore prioritization will help us to have steady measured steps. Identify business processes that present the quickest most meaningful wins and consider them as the earliest automation initiatives. The good news is: other initiatives can wait :)

     To conclude, implementing automation is definitely one big leap an organization could take. There is no doubt that a wise, timely implementation of the advancement will greatly benefit an organization. What it takes to get that wise, timely automation is a mindful slightly uncomfortable “pause and think” moment of what and when to automate. In most cases, what sets the successful automation implementation with the rest is that "pause and think" moment, which unfortunately seems unattractive in this fast-moving world.

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Reference: Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. A. (2018). Fundamentals of business process management (2nd ed.). Springer Berlin.

P.S.:

1. What I enjoyed the most about studying master’s degree, besides meeting great minds, is how my knowledge is constantly challenged. When I'm proved wrong, I am happy knowing that through that process, I am a bit closer to knowing rightness. When I realize my knowledge is shallow, I enjoy deepening it through constant challenges. I think that’s the essence of a master’s degree: to make someone think a tad deeper and act a tad more purposefully. I am most grateful for those things.

2. Credit to my lecturers, George Joukhadar and Frieda Maher, who inspired me to think about automation deeper. Forever, it changed the way I think about automation.

3. After a long thought about this blog’s direction, finally I come up with #sensibletech, a section I dedicate to address my concerns regarding the thoughtful utilization of technology. Please look forward to more #sensibletech posts I will deliver in the future :)

“Through 2022, only 20% of analytic insights will deliver business outcomes.” (Gartner, 2019)

My take: It’s good to have a high ambition but more importantly to have the right ambition. It's good to start by "We want to have data analytics projects/use cases. What should we analyze?" (as long as business values are the objectives), but the better path is "This is our objective, thus X and Y values should be created. What analytics should we perform?"

My personal note: I know the title is a bit controversial. Please don't get me wrong. I always think data science is awesome. I am also a big supporter of analytics implementation. Here is just a piece of my thought on creating better analytics  :)

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Data is widely considered this century’s most valuable asset—beating oil, gold, and anything precious in world history. The attention has been gathered and the spotlight has been shone on its ability to drive business decisions. The four-letter word now has another buzzword: data-driven. 

The dream of becoming data-driven is basically on almost every organization's wish list. When an organization implements a data-driven approach, it means the strategic decisions are based on the analysis and interpretation of data. The insights, patterns, and anything behind the data will be uncovered to decide the actions. So now, that we have data (tons of it!), we all should jump to the analytics, right?

Unfortunately, history repeated itself. Data analytics, as its technological advancement predecessors, is treated as a black box: as if it, by itself, will magically solve all the problems.  In fact, the analytics process as a standalone is far from wizardry. There are a bunch of processes going behind the curtain to ensure that the results benefit us. There are a plethora of details that hold more meaning than the tools and techniques: data governance maturity, analytics strategy clarity, translation and communication effectivity to name a few--business objectives to name the paramount. 

In short, neither having data nor performing analytics sets an organization apart from the rest. The success indicator of analytics is not having use cases but gaining business value. Therefore, it should first and foremost be about action and value (Schmarzo, 2020). Values should always be the heart of every process, including analytics, performed by an organization. Consequently, every analytics should always be able to be converted into value. Value creation means we start our analytics with a clear vision. Always have a business improvement opportunity/problem statement in mind. Instead of wanting to have a data analytics project, ask ourselves, why do we want to have one? What problems/improvements do we want to get the answer about? Invariably, have an objective regarding what should be generated through a use case before creating one.

Many publications including Gartner reported that most analytics projects failed. Let’s not be surprised that the reason wasn’t that the organizations lack use cases/projects/techniques/tools. No, it was not. After careful observation, it was revealed that many organizations didn’t start with a clear vision and objectives. That particular approach is inherently prone to failure in delivering business outcomes.

In conclusion, always know what business value our organization wants to generate through analytics. The clearer our vision, the better.  From there, we know what data should we collect, the data governance maturity level should we aim for, which analytics strategy should we implement, and which use cases should be prioritized. (Yes, we have to prioritize them. It means, not every data set should be turned into a use case exactly now. Some can wait. Some can wait even longer.) 

Back to the title above: "data analytics is overhyped". It will continuously fail to keep up with the hype as long as it doesn't put "value creation" at the center. Ultimately, an organization should be value-driven at the core. Always. Without exception.

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References:

Schmarzo, Bill. 2020. The Economics of Data, Analytics, and Digital Transformation. Birmingham: Packt Publishing Ltd.

White, Andre. 2019. “Our Top Data dan Analytics Predicts for 2019". https://blogs.gartner.com/andrew_white/2019/01/03/our-top-data-and-analytics-predicts-for-2019/. Accessed on 26 March 2022

image source: umanitoba.ca

In case you only have 15 seconds to read this *wink, here’s the summary: to remain grounded amidst a sea of flashy buzzwords is a luxury.

I got inspired to write this on my way back from buying my favorite seblak (a Sundanese savory and spicy dish with wet crackers as the main ingredient) while raindrop was suddenly pouring over me. I saw some people had to work under the rain with nothing on top of their heads. Under this kind of circumstance, it is a luxury to be able to rush home and worry about nothing. Wait. I said luxury? Why did this word instead of privilege pop up in my mind?

Ever since I don’t exactly remember when, I rarely call something that not everybody has access to/opportunity of a privilege anymore. I used to call everything which wasn't near to a problem for me but still was considered one for some people as a privilege. For example, in this pandemic situation, the option to work from home when some people have to go out to earn money was called a privilege. Now I name it a whole luxury.

My standard on luxury has become lower and lower and for me that’s self-betterment. I realized that even the “basic requirements” in my life are out of the range of some people. A roof over my head, clean clothes, 3-meals a day, health facilities, internet access—who says everyone has access to them? Tertiary education experience, a stable job—the opportunities I casually didn't deem beds of roses. The realization I got from thinking about them humbled me every time.

(P.S.: I recently came across an article about global education statistics *tried to post the link but I can’t find it again. Globally, the percentage of individuals with college degrees was less than 8%. I was taken aback. Indeed, the saying "privilege is invisible to those who have it" was also applied to me and I felt sorry about that.)

From time to time, the list of what I called luxuries simultaneously expanded and shifted. Back then when I was a teenager, everything extravagant is a luxury. When I entered college, I remember mentioning having idealism as a luxury. I also remember saying that finding what you genuinely want to do in life as early as possible (and even better if we can live according to the results) is a luxury. Some years ago, because I found that being left with no choices could be a thorny situation, having choices slid up on my “what are luxuries” leaderboard.

Now, as I work in the information technology field, there is something I would like to call a luxury: the ability to remain grounded amidst the sea of flashy buzzwords. We live in an era where we hear (and maybe use) a fair amount of jargon. In the period where someone is regarded as knowledgeable when they mention sophisticated tech terms, it exerts oneself to be undistracted. 

After some people (especially the influential ones) talked about the tech buzzwords, what usually happened next is those things seemed too splendid to be unimplemented. The truth is, I have seen a lot of cases where technology implementation was rushed while the fundamental stuff was nowhere near steady. I've witnessed that technology adoptions were done hastily just because they were fancy yet no one carefully analyzed/calculated the cost and benefits in advance. I’ve heard here and there that the necessary requirements to make them effective hadn’t been established while the decision to invest in the new technologies was made. I wouldn’t even go deeper with the benefits realization and investment payback because in that kind of situation, what do we expect? :)

(Have you ever seen memes of a boy trying to skip some stair-steps which were widely used to represent how humans sometimes skip the important parts for whatever "shiny" stuff represented by the step which was aimed to? High five if you laughed over them 😊).

I know to be updated with technology advancement information is something highly necessary. I agreed that it’s essential to understand what’s going on in the tech world so we could react appropriately—anticipate and respond to the risks and/or leverage the tech in case it is beneficial. However, to be easily dazzled by the buzzwords and lose sight of what’s truly important is something I consider harmful. Imagine investing a great sum of money on something for the sake of following the trends while the expected benefits are uncertain and the risks haven’t been properly assessed (or even more addressed).

For those reasons, I can say that the ability to remain grounded amidst the sea of fancy buzzwords is a luxury. The ability to prioritize the fundamental things while having the serenity to not feel missed out is such a luxury. In the IT world, maybe that’s one of the highest kinds of luxuries ever existed. 

Your "hey I am back writing about IT again even though the IT part is microscopic" friend,

iim 

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*In the tech world, it's not that having the most sophisticated tool that I called a luxurious life, it's knowing what's really needed.

*I remember my high school counselor ever advised the students: ojo nggumunan (don't be too easily impressed). Now I understand its hidden meaning even more.

image source: wallpaperaccess.com