My 3 takeaways from Agastya’s “Student, teacher, and AI” conference at Kuppam

Thanks to my friend Ajith Basu, I got an opportunity to participate in the “Student, teacher, and AI”, a national conference held at Agasty’s beautiful Kuppam campus. I was part of the facilitation team with Shriram Bharathan and Suhasini Seelin. The participants came from education departments in the central and several state government offices, schools, colleges, corporates, startups, and NGOs. The conference had 3 thrust areas: (1) demystifying AI, (2) the role of AI in future curriculum, pedagogy, and assessment, and (3) AI's influence on social and emotional learning. Here are my 3 takeaways from my sketchy and selective notes.

Self-learning may be a myth: AI is going to enable self-learning by generating personalized insights. For example, AI can tell the teacher that specific four students are weak in – say “division by 7”. This perspective was championed by Anand Rangarajan of Google among others. Having experienced online self-learning and being a beneficiary of YouTube’s recommendation engine myself, I was drawn to this view. However, Prof Bindu Thirumalai of TISS was vocal in suggesting that self-learning is a myth. Learning is fundamentally a social phenomenon and peer group and mentoring play a crucial role. Having grown up in an educated family and having access to helping friends, could my understanding of self-learning be flawed? I am curious.

Empathy, not yet, but beware of biases today: We looked at a short fictional case where Preetha, a personal artificial assistant, acts as an empathic friend to an 8th-standard girl, Swati, who is struggling with math in the class. Experts felt that most of the technological elements needed for the dialogue are already present. However, the degree of empathy and warmth demonstrated in the story is still missing in the human-AI interaction.

We also explored biases exhibited by Swati and Preetha. While we were doing that Dr. Pradeep from Google fed the story to Bard and showed us how Bard can identify biases participants had not spotted yet. We also reflected upon our own biases we are carrying. During this exercise, most of us were using the term biases to mean prejudices and inclinations. Prof Arun Tangirala of IIT Madras championed a view that for something to be called a bias, we need to have a ground truth and evaluate whether there is a systematic error of judgment. While there were differences in the meaning of bias, there was a consensus that biases will be amplified in the AI world, and it demands greater awareness.

Will AI enable creative adaptive intelligence? Not clear. Ramji Raghavan of Agastya proposed that to live in a world where technology such as AI widens the complexity gap, we need creative adaptive intelligence. Will AI enable it? It is not obvious. Some participants felt that they were already turning to ChatGPT for every problem, and that meant they were becoming lazy. Prof C. K. Manjunath from SMVITM, Mangalore presented how an AI-enabled advertisement such as Titan Eye+ becomes interactive and fun and asked, “How can an average teacher match this creativity?” Ms Changra, the Education Minister from Dharamsala, felt that unless we are alert, technology overdependence may affect our mental well-being.

To me personally, the two high points of the conference had very limited AI in it. One was a play by kids from Ganganagar Government School in Bangalore directed by Suhasini, and the second one was a veena recital by Vidushi. Sujatha Thiagarajan. Both evoked strong emotions. Would an AI-enacted play or an AI-recital in the future have a similar effect? I don’t know.

image credit: Agastya International Foundation

3Cs of idea communication illustrated through Andrej Karpathy’s LLM talk

Communicating your idea effectively is important be it to customers, team members, or investors. We presented 3 attributes of idea communication – curiosity, concreteness, and credibility in our book “8 steps to innovation”. In this blog, I would like to illustrate the 3Cs using Andrej Karpathy’s talk “Intro to large language models” which he published on his YouTube channel.

Andrej Karpathy is one of my favorite teachers in the deep learning area. The OpenAI founding member and ex-director of AI at Tesla has a hands-on approach to teaching involving Python, Pytorch, and technical papers. Hence, I was surprised when Andrej uploaded a PowerPoint presentation on his YouTube channel. I was familiar with half the information in the talk. And yet, there was a lot I could learn from the way Andrej presented. It is an excellent example to illustrate how 3Cs – curiosity, concreteness, and credibility improve the effectiveness of a presentation. Let’s look at each C one by one.

Curiosity: A good presentation not only makes you curious early on, it keeps you engaged by maintaining a curiosity flow. What does curiosity flow in Andrej’s talk look like? He begins with the question, “What is an LLM?” (21 min), then he moves on to the second part, “The promise and future directions of LLM” (17 min), and in the third and last part, Andrej talks about “the challenges in LLM paradigm” (13 min).

Within each part, Andrej is maintaining a curiosity flow. For example, while explaining what an LLM is, Andrej asks questions like “How do we get the (neural network) parameters?” “What does a neural network do?” “How do we obtain an assistant?” etc. While presenting the future directions in LLM research, Andrej explains problems like – what is equivalent of system-2 thinking? Or how do we get tree search in chess to language? How do we create a self-improvement sandbox environment for LLM like how it happened for AlphaGo? And, in the final part, he shows how different jailbreaks like “prompt injection” “data exfiltration” or “data poisoning” pose a security challenge for an LLM. In short, it helps to build a curiosity flow while designing an idea presentation.

Concreteness: Large Language Models are high-dimensional and abstract and as Andrej alludes to in the talk, how they work is not fully clear. Hence, it makes sense to use lots of concrete examples to make the concept understandable. And that’s what Andrej does. In many places, he shows how LLMs respond in certain situations by showing how ChatGPT behaves when you prompt it in a particular way. For example, he illustrates the “reversal curse” by showing how ChatGPT answers the question “Who is Tom Cruise’s mother?” correctly while saying “I don’t know” when asked, “Who is Mary Lee Pfeiffer’s son?” He gives a demo of how LLMs use tools like browser search, calculator, and Python libraries to solve a given problem and present the information as a plot. 

Andrej also uses several metaphors or analogies to explain concepts. For example, he says an LLM is like a zip file of the Internet, except that it is a lossy compression. Or, LLM is not like a car where you can understand and explain how different parts work together to give its function. Or, current LLMs are like speed chess which uses an automatic and fast system-1 mode of thinking, and while it is yet to learn how to solve problems like competitive chess where players use deliberate, slow, system-2 mode of thinking involving tree search.

My biggest takeaway from the talk comes in the form of a metaphor when Andrej explains that it is better to think of an LLM as the kernel of an emerging operating system (like Windows or Linux) rather than as a chatbot or a bot generator. To explain this, he maps various components of current OSes to LLM components. For example, he says the Internet is like the hard disk in the traditional OS, and context window is like the working memory or RAM, etc. I thought it was a powerful metaphor to convey the paradigm shift.

Credibility: Most idea presenters like you and me need to worry about making our ideas credible. Given his position and brand and given the popularity of LLMs, Andrej probably doesn’t have to pay special attention to this aspect. However, he is making forward-looking statements in this talk, and he needs to ensure he doesn’t divulge any information confidential to OpenAI. He achieves this by citing academic papers while mentioning future directions and security challenges. His demo also adds to the credibility. He is not making any “AGI is around the corner” kind of hyperbolic statements and devotes time to talking about the limitations and challenges of the current LLMs.

I hope this illustration helps one to see how the 3Cs - curiosity flow, concreteness, and credibility help in designing better presentations.

Learning from innovation dashboards visible through annual reports

Innovation means different things to different sectors and these differences get reflected in how they present their innovation dashboards. For the past few years, several listed companies in India have started presenting their innovation dashboards either explicitly in the form of a table sometimes titled “intellectual capital” or implicitly through various parameters like new product launches, pilots, kaizens, new initiatives, automations, etc. How do these innovation dashboards look? Let’s look at 4 such dashboards as visible to us through their FY23 annual reports. These companies are Tata Motors, Asian Paints, SBI Life Insurance, and Zomato, and their sectors are automotive, building materials (paints, coatings, and home décor products), insurance, and online food ordering. Please note that the innovation dashboard that gets presented in annual reports is likely to be a subset of what is tracked internally. Disclaimer: Some of these companies are my clients, but here I am restricting myself to data available only through annual reports.

What can we learn and not learn from these dashboards?

• Despite being from different sectors, all four companies had something to report on new products/programs launched in the financial year.

• Intellectual property especially patents and designs are relevant to Tata Motors and Asian Paints but not to SBI Life and Zomato. Tata Motors in India may be learning the nuances of the game from JLR.

• Digital transformation is an important focus area for SBI Life while for digitally native companies like Zomato, it is part of the DNA.

• Automation is an important focus area for all four companies. For SBI Life, underwriting process automation provides a good opportunity for improvement.

• Partners – insurance agents for SBI Life and delivery partners for Zomato play an important role in their business. Improving partner experience is happening through digital transformation for SBI Life while for digitally native Zomato providing offline experience through resting places with drinking water, washrooms, charging stations, WiFi, helpdesk, and first-aid is important.

• R&D expenditure as a proxy for experimentation capacity is visible through Tata Motors and Asian Paints reports but not from SBI Life and Zomato. Tata Motors report mentions they have 11 technology hubs/R&D/engineering centres while the Asian Paints report mentions the strength of the R&D team. Zomato report mentions various pilots like Intercity Legends, Zomato everyday, and reusable packaging. These are experiments which may or may not become successful.

• Continuous improvement must be important to all players. However, systematic efforts are visible through kaizen reporting in Tata Motors and Asian Paints but not in SBI Life and Zomato.

• Automation through bots is visible in the SBI Life report. However, the efficiency of bot usage can come at the cost of customer experience. Currently, the quality of automated responses to customer support queries is poor in most cases. This trade-off is not visible.

• Platform is an enabler of innovation and all four players leverage different types of platforms. Tata Motors has vehicular platforms, Asian Paints has chemical technology-related platforms, SBI Life has digital servicing platforms, and Zomato has an order management platform. However, platform-related metrics are not visible in these reports. We can infer that platforms would have played a role when Tata Motors launched 150 variants in a year.

• Open innovation is an enabler of innovation. Asian Paints report mentions having a technology council with four external members with diverse expertise in various technology areas relevant to the business. Tata Motors must collaborate with other Tata and non-Tata companies, especially in the electric mobility space in creating the ecosystem. However, the related metric is not visible.

In short, there is a lot that can be gathered about innovation from the dashboards available in the annual reports. Innovation dashboard reporting is not a statutory requirement. And yet, it is a good source of input for students of innovation.

Journey mapping tips from Tony Fadell, the father of iPod

Journey mapping is one of my favorite tools to capture customer, employee, partner’s experience journey and identify gaps to enhance it further. Tony Fadell, the father of iPod, has given excellent tips on how he and his team at Nest used journey mapping for experience design in his book “Build: An unorthodox guide to making things worth making”. Here is an attempt to capture some of Fadell’s tips related to journey mapping.

“You should be able to map out and visualize exactly how a customer discovers, considers, installs, uses, fixes, and even returns your product. It all matters,” Fadell says in the book. When people come to him to show a new product they have built, he asks, “Tell me what’s so special about the customer journey”. If the customer journey is that important, why does it get ignored? Fadell points to the cognitive bias we tend to carry – “We’re wired to focus our attention on tangible things that we can see and touch to the point that we overlook the importance of intangible experiences and feelings.”

Before we look at 3 examples of how journey mapping was used for Nest, let’s look at a journey map template Fadell gives along with possible touchpoints in each stage:

Fadell’s point is that we tend to focus on the “product design” stage at the cost of the other stages. Here are three examples from the Nest learning thermostat design.

The app: In the early days of Nest, everyone was focused on perfecting the thermostat. It involved getting the design, AI, electronics, mechanics, colors, textures, right. The installation, feeling of turning the dial, the glow when you walk past, all this was thought through. Fadell points out that in Nest journey, 10% was website-ads-packaging-in-store display, 10% was installation, 10% was looking-and-touching the device and 70% was monitoring and control on phone-laptop. After the thermostat was installed and working, majority of touchpoints were through the app. And the team had lost track of the app. They had done initial prototypes when the project began but thought it to be the easy stuff they can come back to later. And it got pushed to the end. Fadell admits he became “really loud” to bring team’s attention to the app.

The box: “You should be prototyping your marketing long before you have anything to market,” says Fadell. And that is what they did at Nest. The cardboard box, its packaging, the product name, the tagline, the top features, their priority order – all these were printed on a cardboard box and constantly tweaked and revised. Two personas were created one tech-savvy husband and his wife, the decision maker, dictated what made into the house and what got returned. Nest team was asking questions like, “Why would they pick up the box? What would they want to know? What was most important to them?” There was no thermostat isle in Best Buy, Nest’s first retail partner. Thermostats were not bought by homeowners directly. Best Buy was not going to create a thermostat isle either. So, they collaborated with Best Buy and invented a Connected-Home isle.

The screw-driver: When prototypes of the actual thermostat were ready, they were sent out to people to test. Self-installation was potentially a major anxiety generator. Hence, it was a crucial test. Testers reported that the installation was smooth. Everything is up and running. But it took about an hour to install. That was way more than what the team thought. So they started digging into the installation experience and see where things are taking time. It turned out that the installation itself was not the culprit. The testers spent twenty minutes locating the right tools like the screwdriver. So Nest team decided to include a little screwdriver in the installation kit. And, to their surprise, the screwdriver served the purpose of a marketing tool because people had to use it more often than the actual thermostat.

In short, the app, the box, and the screwdriver are excellent examples of how journey mapping can be used to enhance the intangible touchpoints in a customer’s journey.

Related articles:

Journey mapping illustrated through Dunzo’s order-tracking experience

Image sources:

Nest screwdriver image source: https://bmak.substack.com/p/nest-screwdriver

Nest app and thermostat image source: youtube.com

8-steps after 10-years: Why bother building participation?

It has been 10 years since the publication of our book “8-steps to innovation”. During this time, we got the opportunity to share the framework with various leaders. We also saw the framework being put into practice. Through this series of reflections, I will try to shine a light on situations where the framework might be weak. In this article, I will question the third step – building participation.

The 8-step framework suggests that if you want to build an idea pipeline, create a challenge book first (step 2) and then involve people in participative problem-solving (step 3). For example, if you have a brainstorming session around a specific challenge, you end up generating several ideas. Here are situations where this may not work.

Inventor’s challenge: I have met several inventors who prefer to keep their ideas to themselves. They have no interest in sharing it with their boss or colleagues because they feel they may steal their ideas. Perhaps they have had a bad experience in the past where others took credit for their idea. In my workshops, when we have brainstorms, these people suggest some ideas. And then meet me during the break or send a message to share their pet idea which they are not comfortable sharing with others. I understand the importance of secrecy until you have some form of protection. However, sometimes people end up carrying ideas with them for years without any form of validation. It helps to have a few sounding boards. Is ChatGPT a good brainstorming partner? Perhaps.

Manager’s fear: A few years ago, I wrote about 3 reasons why managers don’t throw their toughest challenge to their teams. The single biggest reason is fear of perceived incompetence. They feel they get paid to solve problems and if they share their challenge with the team, they might be perceived as incompetent. It gives confidence when you solve a problem and get your team to implement your solution. This works best when you have been in the system for a long time and know the domain very well. However, when you start managing an existing team, you may not be the domain expert. And this approach may not work.

Why care about small ideas? Continuous improvement as a systematic approach has been around for over a hundred years. Our book presents stories from Toyota, Titan, and TVS. Many organizations continue to highlight the number of ideas and the number of employees participating in continuous improvement programs in their annual reports. For example, the Asian Paints FY23 annual report says that there were 7000+ improvement suggestions submitted. Having said that I have met several leaders who don’t consider continuous improvement worth the cost. What matters to them are big bets. As a result, participation becomes unimportant. Participation thrives when small ideas are encouraged.

Participation in virtual teams: Virtual teams have been around for a while but their presence increased during and post-Covid era. As people started working from home, formal brainstorms and tea-coffee chats diminished. As video calls started taking time, initiatives focusing on not-so-urgent issues took a backseat. And participation in innovation-related initiatives went down. Getting people to participate in anything other than deliveries became a challenge at least in some organizations.   

In short, participation may be one way of building an idea pipeline. However, there are situations in which participation may not work or one may be uncomfortable sharing the ideas. Perhaps ChatGPT is your partner. Problems may be defined and solved by individuals and implemented through teams if they are the managers. So yeah, skip step 3 if you don’t need it.

Strategic management of technology and innovation 2023: A reflection

Last June to August I got an opportunity to teach the course “Strategic management of technology and innovation” again at IIM Bangalore. I have been teaching this elective for the last five years. The class is a mix of part-time MBA (PGPEM) and full-time MBA (PGP) students. Every time I learn a lot through the process of preparation and class interaction. In this article, I present three things that stand out in my reflection and two questions where my gut feeling was significantly different from the class.

Starting a business, Dunzo, and the art of iteration: During the first half of the course, we explored the question, “How do I build innovation stamina systematically?” One of the frameworks we used was 2-loops of innovation – the idea-to-demo loop validated feasibility and desirability assumptions while the demo-to-cash loop validated scalability and profitability assumptions. We used the 2-loops lens to look at the starting of various businesses like Kodak, Dunzo, Ather Energy, Husk Power Systems, etc. For each iteration, we analyzed four parameters - speed, cost, quality of feedback, and cognitive biases, especially confirmation bias.

Dunzo turned out to be interesting on multiple fronts. It was more relatable as compared to Kodak (hardly anyone had used Kodak camera) and Husk Power (little experience with off-grid villages). For the first six months, until it grew to a few thousand customers, Dunzo was running on WhatsApp. Later it adopted mobile apps, cloud, and analytics. Dunzo also experimented with drone delivery. It was a good example of how a business can start low-tech and iteratively become more high-tech. Founders spoke the language of hypothesis testing and customer focus. Customer and delivery partner experience was also improved over the years. And yet, Dunzo remained in the news for cash crunch and market share erosion throughout the course duration. When asked, which is easier to fix – a broken customer experience or a broken business model? Almost the entire class felt a broken business model was easier to fix. However, we found it easier to find counter-examples for the latter – Dunzo, WeWork, Micromax, and Kingfisher – all had decent customer experience but struggled to fix their business model. In case you have any examples where a broken customer experience couldn’t be fixed, happy to learn from you.

Titan, smartwatches, and the surfing of technology waves: In the second half of the course, we shifted focus to enabling and management of innovation. We restricted ourselves to listed companies and used only secondary sources for discussion such as annual reports, CXO interviews, and quarterly earnings call transcripts.

Surfing a technology wave is not easy, too early and you might create technology debt, too late and you risk losing to the competition. We explored how various companies responded to technology waves – IBM-Internet, Titan-smartwatches, Vimeo-video marketing, Amara Raja Batteries-Li-Ion, Lego-sustainability, Amazon-speech recognition, and AMD-data centers. For example, we asked, “Was Titan late in responding to the smartwatch wave?” This was interesting because 75% of the class wore smartwatches and none had a Titan. So, on the face of it, the answer was obvious. However, as we dug into the reports, we found the answer to be much more nuanced and the game is far from over. We used the "real-win-worth it" framework to guess investment, no-investment, and divestment decisions. For example, we asked, “Was it real, win, or worth it criteria that may have led to Ford Motors divesting in Level-5 autonomous car startup, Argo AI?”

AI, creativity, and artificial insight: When the course began in June, ChatGPT hangover was still lingering. I didn’t change the nature of assignments or projects. However, referencing norms became stricter. The fact that AI is going to be a powerful force going forward was given. The challenge for me was to show how to see through the fog and hype. This is where guest lectures helped. Ravi Aranke showed how to use ecosystem tracking – users (individual and paid), startup investments, enterprise adoption, regulatory bodies, expert conversions (experts shifting their opinions), and professionals (marketing, lawyers, doctors, CAs, recruiters) to create one’s view. Sunil Mishra showed how one can build a local chatbot using Python’s langchain library and highlighted generative AI’s banking uses-cases.

We looked at the surprising move 37 during AlphaGo vs Lee See dol 2016 Go game and asked, “Was move 37 creative?” It was one of the moves which the professional Go players thought as a mistake at the first sight and then realized it was part of an intentional strategy. Almost the entire class felt that the move 37 was not creative. Personally, I felt the move was creative, but it also created an opportunity to learn about what creativity means to different people. I also tried to give a glimpse of how Karl Friston shows curiosity and insight can be simulated by synthetic agents using active inference framework. Of course, active inference is primarily used to explain natural intelligence but he and other researchers have also put forward a proposal for how it may lead to distributed super-intelligence.

A potentially game-changing emerging technology which I thought I could spend some time on was genetic engineering - CRISPR, prime editing, etc. Unfortunately, I fell short on my preparation as well as the availability of time. However, I managed to use fiction for the first time as a source of use cases. We looked at a short case prepared from Kazuo Ishiguro’s novel “Klara and the Sun” to classify use cases into current, near-future, distant future / impossible buckets. Ishiguro’s novel unfolds on the backdrop of AI, robotics, and genetic engineering.

Tracing mindfulness word to its Pali/Sanskrit counterparts: Sati and Vipassanā

In my workshops on mindfulness, it is common to get the question, “How is the mindfulness you teach related to Buddhist practices?” So far, my answer has been, “Both involve learning to see clearly”. I know this is a handwavy answer so I decided to explore the question by looking at its counterparts in Buddhist texts to get a better understanding. In this article, I take two Pali/Sanskrit words which are translated as mindfulness, namely Sati (Smriti) and Vipassana (Vipaśyanā), and look at their meanings. But before we get to these source words, let us place the current usage of mindfulness in a broader context.

The word mindfulness means different things to different people, just like innovation. Four types of usages are common: (1) as a practice anchored in Buddhist texts (2) as a secular discipline with a loose to no connection to Buddhist texts/practices (3) as a clinical/therapeutic intervention for mental health issues such as depression; and (4) as a fitness tool like yoga also available on mobile apps and smartwatches. I have been a student of mindfulness of the second type (secular discipline with a loose connection with Buddhist practices) for the past twenty-five years and a teacher for the past eight years. My book “Mindfulness: connecting with the real you” came from this perspective.

As we look at Pali and Sanskrit words for mindfulness, we must note that these are not the only languages in which mindfulness can be traced. Chinese, Tibetan, Korean, Japanese, and perhaps other languages also offer rich sources of old Buddhist texts and would carry words that are translated as mindfulness. I am restricting the scope to Pali/Sanskrit due to my ease of understanding terms and texts in these languages. 

The two Pali (Sanskrit) words we will look at are: Sati (Smriti) and Vipassana (Vipashyana)

Sati (Smriti): In 1881, T W Rhys Davids, an English scholar of the Pali language and founder of the Pali text society, translated the seventh of the Noble Eightfold path sammā-sati as “right mindfulness, the watchful, active mind” [1].  Literally, the Pali word sati or Sanskrit smriti means memory, however, Rhys Davids knew the intended meaning in the Buddhist texts goes beyond just memory. He wrote, “In No. 7 (samma-sati) sati is literally 'memory' but is used with reference to the constantly repeated phrase 'mindful and thoughtful' (sato sampajâno); and means that activity of mind and constant presence of mind which is one of the duties most frequently inculcated on the good Buddhist."[2]

Satipaṭṭhānā Suttā is one of the most used Buddhist texts as a source for mindfulness [3]. It presents four establishments of mindfulness – cattaro satipaṭṭhānā [4].

Kāye kāyānupassī …vedanāsu vedānanupassi…citte cittānupassi…dhammesu dhammānupassi viharati ātāpi sampajāno satimā, vineyya loke abhijjhādomanassaṃ.

To live witnessing the reality of body as body…feelings as feelings…mind as mind…phenomena as phenomena, ardently, with clear comprehension, with awareness, keeping away from craving and aversion towards the world.

In this commonly occurring phrase, sati is translated as awareness. However, the word sati is always accompanied by anupassanā and sampajannā. Bhikkhu Bodhi translates them as observation and clear comprehension respectively while S N Goenka translates them as witnessing and wisdom of arising and passing respectively. In either case, when mindfulness is meant to capture the essence of Satipaṭṭhānā suttā, it makes sense for the word to carry the shades of sati, anupassanā and sampajannā.  

The following verse from Dhammapada (Pali verse no. 374) also brings out the close relationship between sati and wisdom of arising and passing [5].

yato yato sammasati, khandhānaṁ udayabbayaṁ, labhatī pītipāmojjaṁ, amataṁ taṁ vijānataṁ

Whenever he sees with insight the rise and fall of the aggregates, he is full of joy and happiness. To the discerning one, this reflects the Deathless. (Translated by Acharya Buddharakkhita [6])

Vipassanā (Vipaśyanā): Mindfulness is also used as a translation of the Pali (Sanskrit) word Vipassana (Vipaśyanā). It literally means seeing clearly or seeing in a special way. It is also translated as insight. S. N. Goenka defines it as [7]:

Paññatti ṭhapetvā visesena passati’ti vipassanā

Having removed the apparent truth, seeing things by their characteristics.

Vipassana represents a meditation tradition that got started in Burma (Myanmar) in the 18^th century and spread among monks as well as laypeople in the 19^th and 20^th centuries in Burma, Thailand, and subsequently across the world [8].  These traditions use both samaṭhā (tranquillity) and vipassanā (insight) by placing varying degrees of emphasis on the two aspects [9]. However, many old Buddhist texts use these two words together. For example, in one of the discourses in Samyutta Nikāya (SN 43) Buddha says [10]:

Katamo ca bhikkhave asaṅkhata-gāmī Maggo? Samatho ca vipassanā ca.

And what is the path that leads to the unconditioned? Tranquility & insight…

If the objective of Vipassana is to see clearly, we can ask what is it to be seen clearly? The answer differs somewhat based on the tradition. However, three characteristics, tilakkhanā (trilakśanā) are common, especially in Theravada tradition: namely anicca (impermanence), dukkha (unsatisfactoriness), and anatta (no self). For example, verses 277, 278, and 279 from Dhammapada express this:  

sabbe saṅkhārā aniccā ti, yadā paññāya passati, atha nibbindatī dukkhe esa maggo visuddhiyā (277)

“All conditioned things are impermanent” - when one sees this with wisdom, one turns away from suffering. This is the path to purification. [11]

sabbe saṅkhārā dukkhā ti, yadā paññāya passati, atha nibbindatī dukkhe esa maggo visuddhiyā. (278)

“All conditioned things are unsatisfactory” - when one sees this with wisdom, one turns away from suffering. This is the path to purification.

sabbe dhammā anattā ti, yadā paññāya passati, atha nibbindatī dukkhe esa maggo visuddhiyā. (279)

“All things are not-self” - when one sees this with wisdom, one turns away from suffering. This is the path to purification.

For Nagarjuna, the father of Madhyamaka school, as he presents in MulamadhyamakaKarika verse 24.40, seeing just one characteristic that is of śūnyatā or essencelessness in everything is enough and everything else follows from it [12].

To summarize, we looked at two Pali/Sanskrit words – sati and vipassanā which have been translated as mindfulness. As we saw, in the Buddhist texts, these words are accompanied by other related words whose meanings are also incorporated in the meaning of mindfulness. Phrases like awareness of or seeing clearly into, with a calm mind, the characteristics of human existence such as impermanence, unsatisfactoriness, no-self, śūnyatā stand out.

Sources:

[1] T W Rhys Davids, “Buddhist Suttas, translated from Pali”, Oxford at the Claredon Press, 1881, pg 107.

[2] T W Rhys Davids, pg 145

[3] Bhikkhu Bodhi, “What does mindfulness really mean?”, in “Mindfulness: diverse perspectives on its meaning, origins, and multiple applications at the intersection of science and dharma”, edited by J. Mark G. Williams and Jon Kabat-Zinn, 2015, pg 19.

[4] Achara S. N. Goenka, “Discourses on Satipatthana Sutta”, Vipassana Research Institute, 2013, pg 22.

[5] Anandjoti Bhikkhu, “A comparative edition of the Dhammapada”, 4^th revised edition, April 2020, pg 221.

[6] Acharya Buddharakkhita (translator), “The Dhammapada: The Buddha’s path of wisdom”, Buddhist Publication Society, Kandy, Sri Lanka, 1985, pg 80.

[7] Achara S. N. Goenka, “Discourses on Satipatthana Sutta”, Vipassana Research Institute, 2013, pg 4.

[8] Patrick Pranke, “On saints and wizards: Ideals of human perfection and power in contemporary Burmese Buddhism”, Journal of International Association of Buddhist Studies, vol 33, 2010, pg 453-488.

[9] Bhikkhu Analayo, “The dynamics of Theravada insight meditation”, Zhuang Guobin (ed), Dharma Drum Publishing, Taiwan, 2012.

[10] The Sri Lanka Buddha Jayanti Tripitaka Series, Digital edition, 1995, SN 43.2

[11] Acharya Buddharakkhita (translator), “The Dhammapada: The Buddha’s path of wisdom”, Buddhist Publication Society, Kandy, Sri Lanka, 1985, pg 65

[12] Nagarjuna’s sunyata through Mulamadhyamakakarika verses, October 2022

image credit: Gauri Dabholkar