Have you ever considered the possibilities of Artificial Intelligence, specifically the capacities of Generative AI? If your work revolves around the nonprofit sector, this question is more than just theoretical musing. It could guide you towards a tool that has the potential to boost your efficiency considerably.

So, what is Generative AI? It's a branch of machine learning where the algorithm, through training on the available data, learns to produce something entirely new. This is not simply a matter of repetition or duplication. The AI creates something unique, inspired by learned patterns, similar to a child creating unique drawings after observing some examples. In its own domain, Generative AI generates new outputs, such as text, images, or even music.

Generative AI isn't just a fleeting tech buzzword. It's here, and its capability to enhance productivity is not just a promise, but a reality that's being experienced today.

This technology holds immense potential, particularly for nonprofit organizations. They often face significant resource challenges. Most nonprofits embark on their mission with a human resource deficit. What if this deficit could be addressed with Generative AI? What if Generative AI could help with routine tasks, enabling your team to dedicate more time to mission-critical responsibilities? Imagine serving your community more effectively, generating insightful reports, or executing impactful campaigns, all while your team spends less time on mundane tasks and without any job displacement.

This illustrates the transformative potential of Generative AI for the nonprofit sector. The goal isn't about replacing humans, but assisting them, enhancing their potential. It's about empowering your team, improving efficiency, and optimally utilizing resources without threatening jobs. So, let's delve into the possibilities together.

8 Practical Ways Generative AI Can Boost Your Nonprofit's Output

Generative AI is a potent tool that can supercharge a nonprofit's output, streamlining operations and speed up task completions. It's worth noting that as of June 2023, these steps involve patching multiple solutions together. But soon, more seamless solutions will be available (see Microsoft 365 Copilot and AI-powered Google Workspace).

Let's walk through eight example uses of generative AI. Keep in mind that each step requires a conversation with your generative AI and iterative improvements to get the best results.

1. Writing Standard Document Templates

From proposals to agreements and policies, consistency is key. Generative AI can help nonprofits create standardized document templates. It can draft standard documents based on your specifications and save time that would otherwise be spent crafting these from scratch.

2. Social Media Posting

A strong social media presence is crucial for any nonprofit. Generative AI can support this effort by generating engaging and relevant content tailored to your target audience.

In the example below, I use Microsoft Designer to quickly design an Instagram post to urge donors to sponsor a mentee. First, I asked Microsoft Designer to generate an image using the prompt “Donation to sponsor a young person, in line drawing, pastel color”

Then I asked it to create the Instagram post with the prompt: “Instagram post to urge donation”

Microsoft Designer generates a few ideas which you can easily tweak and adjust further.

3. Meeting Minutes Generations

If you already have your meetings online, many popular online meeting platforms offer built-in transcription capabilities, including Google Meet, Zoom, and Microsoft Teams. Alternatively, you can integrate third-party transcription services like Otter.ai or Fireflies.ai to automatically transcribe your meetings.

After obtaining the meeting transcription, navigate to the generative AI interface (such as ChatGPT), and paste the transcription into the input field. Prompt the AI to generate meeting minutes from the transcription.

Here's an example.

4. Content Creation

Generative AI's capacity for varied content generation is vast. It's proficient in crafting engaging newsletters, sincere donor appreciation emails, and persuasive outreach emails for potential partners. Its ability to craft captivating narratives can effectively convey your organization's objectives and requirements in grant applications, thus increasing your chances of receiving financial support.

For educational content, generative AI can develop a diverse array of materials, such as lessons, quizzes, and tutorials. In the following example, I asked ChatGPT to create the training material content based on the key messages in my training. As ChatGPT can't generate presentation slides directly, I copied its output to PowerPoint and let it design the slides for me.

5. Data Analysis

Nonprofits often work with intricate datasets—encompassing donor data, campaign performance metrics, and more. Here's where generative AI can lend a helping hand. Given clean, standardized data, it can analyze this rich trove of information and generate insightful reports.

Consider the following example, where I utilize ChatGPT to analyze a survey result. Initially, I prepare the data by exporting it from Excel to a text-based format (CSV), ensuring it's clean and standardized. I then prompt ChatGPT to perform sentiment analysis and display the results in table format.

6. Volunteer Recruitment

Generative AI has significant potential in optimizing the process of volunteer recruitment. With a solid understanding of your nonprofit's mission, goals, and needs—learned by analyzing existing data and documents—the AI can craft job descriptions that accurately represent the roles you need to fill. The descriptions can highlight the necessary skills, tasks, and the impact potential volunteers could make, thus attracting the right individuals to your cause.

In the following example, I ask Google Bard to write a job description that is appropriate for the role and for the nonprofit.

7. Performing “Matching Algorithm” Tasks

Generative AI can play a valuable role in “matching algorithm” tasks, such as mentor-mentee pairing. ChatGPT can process the data you give it, extract relevant information, and generate potential matches based on compatibility metrics.

In the following example, I ask ChatGPT to propose pairing of mentors and mentees based on various factors like career interests, domain expertise, and personal preferences to identify suitable mentor-mentee pairs. This technology can save significant time and effort in the initial stages of matching, providing a more efficient and effective way to connect mentors and mentees.

7. Performing “Matching Algorithm” Tasks

Generative AI can be remarkably effective in various “matching algorithm” tasks, including mentor-mentee pairing, donor-volunteer matching, and aligning resources with projects based on relevance and need. It operates by processing the data provided, extracting pertinent information, and generating potential matches using compatibility metrics.

For instance, in the context of mentor-mentee pairing, ChatGPT can consider various factors like career interests, domain expertise, and personal preferences to identify suitable pairs. In the following example, I ask ChatGPT to propose pairing of mentors and mentees based on these factors.

8. Ideas Generation for Strategic Roadmap

Strategic planning is a cornerstone for any organization's success. While it's ultimately the responsibility of your senior leadership to shape the strategic roadmap, generative AI can be an invaluable ally in this process. By feeding it relevant information—such as your mission, vision, and internal strengths and weaknesses—AI can generate a plethora of innovative ideas for long-term growth. It's like having a brainstorming session where AI provides an array of fresh perspectives based on the data it has been trained on.

In the following example, I use Google Bard to generate such ideas.

Implementation Considerations

Incorporating Generative AI into your nonprofit organization requires careful thought and planning. Here are some important aspects to consider:

1. Viability of AI Partners

As with any emerging industry, the AI landscape is dotted with numerous service providers. While this presents an array of choices, it also implies potential volatility. Many of these companies might fail, cease operations, or merge with others. Therefore, it's crucial to select a stable and reliable AI partner. Look for providers with a proven track record, strong customer testimonials, and a clear vision for the future. Your chosen partner will play a pivotal role in your AI journey, so choose wisely.

2. Data Privacy and Security

As we harness the formidable capabilities of AI, we must not forget our crucial responsibility towards data privacy and security. To mitigate risks associated with data handling, it's imperative to employ AI solutions that comply with established privacy regulations, such as the General Data Protection Regulation (GDPR) and Personal Data Protection Act (PDPA).

Ensure that any data you provide to your AI service provider aligns with these regulations and is consistent with the agreements you have with your customers or stakeholders. Additionally, it's crucial to anonymize sensitive data to protect individuals' privacy. Remember, robust security measures are not just best practices—they're absolutely essential when dealing with sensitive data.

3. Accuracy and Dependability

The allure of new technology can sometimes make us overlook the basics, such as the accuracy and reliability of the results. Never lose sight of this aspect. Verify the results of your AI systems regularly, and fine-tune your prompts as needed to ensure they provide dependable outcomes. Make this an integral part of your AI strategy.

4. Continual Learning

The journey with AI is not a one-off project, but rather a continuous process of learning and improvement. It's not something you set up and forget. Instead, you need to constantly use it, experiment with it, and iteratively improve upon it. Work on your prompts, explore new use cases, and continually refine your approach. As you keep learning and experimenting, you'll find new ways to integrate AI into your operations, making it more valuable over time.

These considerations will guide you in effectively implementing generative AI in your nonprofit, helping you leverage its full potential while minimizing potential risks. Remember, the journey with AI is a marathon, not a sprint. Approach it with patience, persistence, and a commitment to learning, and you're likely to reap significant benefits.

Conclusion

The transformative potential of Generative AI for nonprofits is not a distant promise; it is a reality today. From accelerating routine tasks to generating ideas for strategic direction, Generative AI has the power to revolutionize how nonprofits operate. It's about turning resource constraints into opportunities, augmenting human potential, and ultimately driving more impact.

The adoption of Generative AI in nonprofits is not just about technological transformation; it's about improving services for beneficiaries and revolutionizing user experience. It presents opportunities for new business models and innovative ways to deliver value. And this is just the tip of the iceberg; ongoing innovations in Generative AI aim to make its adoption even more seamless and intuitive.

So, what's the future for your nonprofit? I encourage you to start exploring the capabilities of AI, find avenues to streamline daily tasks, and consider how AI can significantly improve your service delivery. Remember, it's about leveraging AI to augment your human resources and provide a superior experience for those you serve.

Embracing AI is an ongoing process of exploration, learning, and refinement. As a Fractional CTO with experience in Generative AI implementation, I've witnessed the significant shift it can bring. Navigating this space may seem challenging, but it's not something you need to tackle alone. I am here to support you, providing insights and guidance, as you discover how Generative AI can serve your organization's unique needs. If you have any questions or if you're ready to explore the potential of AI for your nonprofit, don't hesitate to reach out to me.

Here's a funny video of Bill Gates, 27 years ago, struggling to explain the internet's potentials to Dave Letterman (starts at 3:10). Dave played it wittily for the audience, but his skepticism towards the internet, as a layman, is fully justified.

NFT and web3 have certainly created a lot of debates and discussions among the digerati. I haven't found a good explanation on why NFT is better than the solutions we have today. But I think it's because my 2022 brains cannot perceive what technology we will have in 27 years.

Hey, even a genius like Bill Gates could only see the internet as online magazines and chat rooms in 1995.

#technology

Earlier this month, I discovered another app in the read-it-later category called Matter. Although Matter is less than two years old, it already has features I did not know I wanted from Pocket. I also found its user interface to be very thoughtful and well designed. After a couple of hours of using Matter, I was convinced. I replaced Pocket with Matter on all my devices.

My experience above illustrates that there is rarely a winner-takes-all in today's business world. In a platform economy (such as ride-sharing and food delivery), while the incumbents may have years of market leadership, a new competitor can launch quickly at a low cost. There is rarely price competition because most apps have a free tier. As a user, I can always switch to a different app quite easily.

Back to Matter. As a startup founder and product designer, I enjoyed reading this interview with Ben Springwater, one of the founders of Matter. Some takeaways from the article made me think they will be a new market leader in the read-it-later app space.

First, Ben Springwater founded the company to scratch his own itch. He was a heavy online reader and one of the top users of Pocket. Still, he was not satisfied with Pocket and decided to build a better solution. As a founder, a personal connection with your product can fuel your drive when things get rough (as most startups in the early stage).

Second, he has a clear point of view about the problem and the solution to fix it — not just a cursory idea of building a new app. As the internet evolves, our online reading patterns also change. Now our reading contents come not just from blog articles but also podcasts, Twitter threads, and newsletters. Matter was built for these new realities, while Pocket has not improved much since it launched a decade ago.

Third, Matter knows their target audience: serious readers who care about curation and triage of good content. I am one of their target users, and the experience I had when I first discovered Matter is precisely what they aim for. By understanding the target users, Matter was able to design the whole onboarding process and gave me a great experience.

I wrote this post about a read-it-later app, but it's also a microcosm of today's business world. Technology has accelerated the ability to build and launch a new business. You will get overtaken by a new entrant if you're not always on your toes. To quote Andrew S. Grove, “Only the paranoid survive.”

#productivity #startup

I went to the University of Michigan in 1994 and became a fan of their football team since then. Since I came back to Indonesia in 1997, it has not been easy being an American football fan in this part of the world. Besides the non-existent fan community, the time zone difference makes it hard to watch games.

As a Michigan Wolverines fan, my best day this year was the 28th of November (the 27th in the US). It was the day when we beat our heated rival Ohio State Buckeyes for the first time since 2011 (and only the second time since 2003). I woke up at 2 AM that day to watch the game. Although the season had been going quite well up to that point, most Wolverines fans, including me, suffered from PTSD after years of beating and had little expectations for the game. The Buckeyes were also having an excellent season and came into the game ranked number 2 in the country. Well, this year turned out to be different. By the time the game ended around 4:30 AM, I was so happy I might have cried a little.

After defeating Ohio State, Michigan beat Iowa to win the Big Ten Conference for the first time since 2004. 2021 has been a storybook of the ages for Michigan, and the story of this team starts with their head coach, Jim Harbaugh.

Harbaugh was already one of the top coaches at the professional football level (NFL) before he decided to coach his alma mater in 2015. At that time, Michigan had been mediocre-to-bad for almost a decade. The university appointed him a savior and gave him one of the highest salaries for a head coach. He had two big tasks: return the football team to glory and beat Ohio State University.

Lesson 1: There is no end to continuous improvement

Jim Harbaugh was a good coach before he started at Michigan, and he continued to be a good coach there. In his first season in 2015, he immediately brought Michigan back to a nationally-ranked level. He started strong and continued to field good teams year after year. His most significant shortcoming had been his poor record in beating Ohio State.

Undeterred, Harbaugh kept making tweaks to his coaching staff and football strategy. Year after year, he was not afraid to make a change when proven wrong. In 2016 he hired Don Brown, one of the top defensive coordinators in the country at the time. From 2016-2019, Michigan's defenses rank in the top 10. By most counts, Don Brown was a good hire except for what matters the most: helping Jim Harbaugh beat Ohio State. With victory eluding him, Harbaugh made another coordinator change in 2021 and brought in Mike Macdonald. Macdonald brought youthful energy and a new defensive scheme, which proved to be the missing ingredients for beating Ohio State.

On offense, Harbaugh made the team much more physical in 2021. His offensive team relies on a balanced attack and does not depend on the quarterback to be a superstar. The team also grew better throughout the season, from the first game in September until their last in early December.

Lesson 2: Keep the faith and stay the course

When you're one of the highest-paid coaches in the country and when millions of people watch your team play on Saturdays, your performance is bound to be put under the microscope. When the result falls below expectations, people forget about your efforts and over-emphasize your mistakes.

Looking back, many of Harbaugh's losses to rivals were due to freak plays and bad luck. In 2015, the team lost to Michigan State University because of poor handling of the ball in the last 10 seconds of the game (see this one-in-a-million-chance tragic comedy plays out in this video). In 2016, the team lost to Ohio State because Michigan's quarterback (pretty much the most essential player) had to play with a broken collarbone that he suffered two weeks prior.

You have to separate good decisions from bad results. When you believe that you are doing the right things, you must trust that the results will eventually go your way.

When Harbaugh's contract was near ending last year, many Michigan fans wanted him terminated and replaced. Eventually, in January this year, the university and Harbaugh finalized a contract extension with restructured terms. Harbaugh bet on himself and agreed to a lower base salary with performance-based incentives. The bet paid off. With his successes this year, he will make up his reduced salary and more (note: he committed to donating his bonuses to university employees impacted by Covid-19).

Lesson 3: Show your appreciation

At the end of the day, the head coach's success is determined by his staff's game-day preparation and his team's performance on the field. Jim Harbaugh is vocal in elevating the profiles of his staff and players. When TV reporters interview Harbaugh on camera, he turns the spotlight on his players instead and calls out their names. He shows how much he enjoys coaching his team, and his passion rubs off on his players. You can see how much his players enjoy being part of the team.

It's great to be a Michigan Wolverine. Congratulations to Coach Harbaugh for winning 2021 Coach of The Year. We have an upcoming game against the University of Georgia in the College Football Playoff semifinals on the 1st of January, so I already know how I'm spending my New Year's holiday.

Go Blue!

#leadership

In this era of chronic skills shortages, rapid automation, and digital transformation, companies are confronting a growing talent problem, one that has the potential to become a strategic bottleneck. How can they find people with the right skills to do the right work at just the right time? The half-life of skills is shrinking fast, and many jobs now come and go in a matter of years. Not only that, but major demographic changes are under way: Boomers are aging out of the workforce, and Millennials and Gen Z are taking over, bringing with them very different priorities about who should do what work—and where, when, and how it should get done.

To help companies address these challenges, a new generation of talent platforms—such as Catalant, InnoCentive, Kaggle, Toptal, and Upwork—has emerged. In contrast to Uber, Amazon Mechanical Turk, and TaskRabbit, these platforms offer on-demand access to highly skilled workers, and our research shows that their number has risen substantially since 2009, from roughly 80 to more than 330. Much of that growth took place during the past five years alone. Today almost all Fortune 500 companies use one or more of them.

I've been watching the developments of the on-demand workforce lately and I fully believe it is going to be the next big thing in business. I read the Gig Mindset earlier this year and the book was weak in explaining how companies can take advantage of gig workers. This HBR article fills a lot of the gaps in the book.

Today we have departments inside companies dabbling and experimenting with on-demand workforce. I think, soon, on-demand workforce will be a key component in the enterprise strategy. We already have the drivers in place:

• Greater need to innovate while facing difficulty in finding talents to do it
• Fluctuations in headcount needs because the nature of innovation projects are “experiment and fail-fast”
• Increased comfort level of working with remote workers due to Covid-19

And finally, on-demand workforce is how startups and small businesses can compete against big companies. Without a large HR department and a budget to lure talents with high salaries, startups and small businesses will use gig platforms like Toptal, Clarity, and Catalant.

#bookreviews

Humans are living longer and longer. The majority of children born in developed countries today can expect to live to more than 100 years. Many of us reading this article will work until our 70s and 80s. At the same time, the world is changing quickly, so we must always adapt, grow, and learn new things.

However, even if you have decided to block some time for continuous learning, you have another problem. There is an abundance of learning resources out there. What should you learn? What learning resources should you pick? You have limited spare time and you can't possibly learn everything.

Start with WHY

Finding the time to learn is hard. Learning new things and getting to proficiency is hard. Therefore, understanding WHY you're doing these hard things will help you along the journey.

Everybody will have different methods to understand their WHY. I've used a framework from the book Getting Things Done by David Allen, which gives me the following “horizons” to review:

• Purpose and Principles: your big-picture view, such as your life's purpose and why you (or your company) exist in this world
• Vision: your 3-5 years big strategy
• Goals: your 1-2 years plans and targets
• Areas of focus and accountabilities: the knowledge and skills you need to perform better at your job or responsibility
• Current projects: the knowledge and skills to do your work today

Build a framework of WHAT you want to learn

When it comes to learning, Elon Musk is a person that I really admire. As an entrepreneur, engineer, and industrial designer, his career is very diverse. Consider that he is founder of X.com and executive at PayPal (financial services), founder of SpaceX (aerospace), CEO of Tesla (automotive and clean energy), founder of The Boring Company (infrastructure and tunnel construction), co-founder of Neuralink (biotechnology), and co-founder of OpenAI (artificial intelligence). It takes skill and discipline to be able to learn such diverse fields of knowledge so that he can lead those multi-million dollar companies.

In 2015, Elon Musk hosted an Ask-Me-Anything session on Reddit. Answering a question about how he can learn so much and so quickly, Elon Musk gave the following answer:

“It is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, i.e. the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang onto.”

To use the tree analogy, learning starts with the tree trunk, then the branches, and finally the leaves. In other words, start with understanding the fundamental concepts of what you want to learn. At this stage, coming up with good questions is more important than answering them.

For example, recently I wanted to learn about the palm oil industry and its impact on environmental sustainability. Typing a few broad search terms on Google (such as “palm oil sustainability”) is always a good starting point to get the brain going. The first few search results whet my appetite to ask more questions, such as: How does the palm oil industry work and what type of companies are involved in it? What are the environmental issues caused by the industry? What is the industry doing to combat this problem?

You can learn faster by connecting new knowledge to existing knowledge. When you are learning a new field, try to relate it to something you already know. Even if the field is something totally new to you, quite often you will find at least analogies to something you know. Having a big repertoire of “mental models” will help you.

For example, I learned that a palm oil industry player can get certified to prove that its products and business practices follow sustainability guidelines. Sustainability certification is very important in the palm oil industry and has a direct impact on revenue. When learning about the certification process in the palm oil industry, I dug into my experience in the audit process in the financial services industry and my university education about manufacturing supply chain. While they are not the same, making analogies between them helped me.

One more tip about building your knowledge tree: As you follow one branch, you will discover other branches. Once I understood the palm oil production supply chain, I wanted to dive deeper into each area and learn more about them. While this is part of the learning process, if you're not careful, you can go down the rabbit hole that doesn't help you achieve your objective. Always go back to the WHY and decide whether you want to go deep or broad in your learning process.

Choose HOW you want to learn

There are theories that different people have different preferences in learning styles. One such theory is the VARK model, i.e. Visual, Aural, Read/Write, and Kinesthetic. However, further studies have shown that the VARK model is merely an indication of preference, not the quality of learning. In other words, anybody can learn using any style.

Personally, I think the best way to learn is by picking the right learning medium for the context. For example:

• Visual: I watch educational YouTube videos when I'm low-energy and just want to do passive learning
• Aural: I listen to audiobooks and podcasts when I'm exercising at the gym
• Read/Write: As I wrote in How I manage the information firehose, I block time every day to do serious reading and writing notes
• Kinesthetic: Some learning must be done by hand. For example, the best way to learn painting is by actually painting.

A word about Just-In-Time vs. Just-In-Case

Congratulations if you are already blocking some time every day to learn and invest in yourself. Now you need to be strategic about how you spend this time.

Be careful about hypes. I work in technology and a lot of topics get over-hyped. I'm sure you've come across many articles about blockchain, artificial intelligence, etc. Don't fall into the trap of trying to learn everything (i.e. Just In Case).

Understand your WHY and treat knowledge like a “semantic tree” so you can decide what to learn and how deep you need to learn. Then, apply Just-In-Time learning by picking the right resources. JIT is very possible today because of online and on-demand learning resources, even for obscure topics — you can find rare books on Amazon, purchase them online, and start reading in minutes.

Regardless of how you learn, don't forget to also reflect and experiment. These two final steps will help your new knowledge to stick.

#systemsthinking #productivity

Back in the '90s, before the internet and the search engine, I used to have to go to my university's library to find information. Today, we have the world's information on our fingertips, and we can find data about almost anything from wherever we are. Our challenge today is not about getting information, but about filtering the signal from the noise and turning that filtered data into knowledge.

The following is how I tackle this challenge.

Step 1: Curate sources of information

Most of us have our regular “channels” from which we get information. These sources may be online (websites we frequent, social media, RSS feeds, mailing lists) and offline (newspapers, books, and magazines).

The first step is to periodically review the sources of information. Ask yourself:

• Are the people I follow on social media still interesting to me?
• Are the websites I regularly visit still giving me valuable information?
• Are the mailing lists I subscribe to still relevant to my needs?

These days, most of my sources of information are online. I want to share a couple of tips about getting information:

• RSS is a way to read the content of a website without actually visiting the website itself. Using software like Inoreader (which is my choice for RSS reader tool), you can “subscribe” to many websites and read all their content in one place. Not all websites support RSS, unfortunately, but many still do.
• Podcast is a great medium to get news and information (and entertainment) without having to use your eyes. I listen to podcasts when I work out and commute — it's probably the only times where I multi-task. I currently subscribe to 32 podcasts and I found PocketCasts to be a great software for managing that many subscriptions.

Step 2: Skim, then read now or save for later

With my mobile phone, I usually get my news and information first during my downtime, e.g. short breaks between important activities or when I'm riding public transport. In this step, I do a light skimming of my information sources. The goal is for broad coverage, rather than depth. I look for clues about whether the information is relevant or interesting to me.

If there is an article that catches my eye, I will decide whether to read it then or save it for later. This will depend on the length of the article, the time I have, and just how compelling the article is. If I decide to save the article for later, I will save it in Pocket, a “read-it-later” tool.

Step 3: Block time for serious reading

This step is very much a habit that I have established. You may have heard of “the five-hour rule,” which says that no matter how busy you are, always block 1 hour every workday to learn something. This practice is critical for my growth as a person and a professional.

The keys to this step are focus (hence blocking the time) and active reading (highlighting passages and taking notes). E-books are great because I can highlight and take notes directly on the e-book itself.

Readwise is a great tool that consolidates your highlights and notes in one place. It integrates well with Kindle, iBooks, and Pocket (among others). Readwise then allows you to review your highlights in the future, so you can remember important passages from the articles and books you have read.

Step 4: Save and file information

After step 3, I will decide whether the article is worth saving. If it is, I will save it on Evernote. I do this because of two reasons:

• Although most information is available on the internet nowadays, there is no guarantee that it will be there forever. Articles sometimes disappear on the internet and the URL may change.
• Like in Step 1, saving the article to Evernote is another act of curation. I have almost 10,000 notes on Evernote now, each has been tagged for easy searching. If someday I need to find a particular information, searching my Evernote will give me better and more relevant information.

Step 5: Connect new information to existing knowledge

In this last step, I block time to think about how the new information is related to the knowledge I already have. To do this, I follow the Zettelkasten method described in Sonke Ahren's book, How to Take Smart Notes.

Zettelkasten is a method to store and organize knowledge, extend your memory, and generate new ideas. With Zettelkasten, you write one note for one nugget of information or idea, then connect the note to other notes. Connecting a note to other notes mimics how the brain learns. I've found that this method has helped me surface meaningful ideas and facts.

We are living in the information age and your brain will be overwhelmed if it must remember everything. As David Allen says, “Your mind is for having ideas, not holding them.” Having a Personal Knowledge Management (PKM) tool is important for this step. My tool of choice is Obsidian.

Final words

Having the right tools to do the above steps are important. What's also important is establishing the habit to do them. If you read for more than entertainment, and if your goal is to manage information and turn it into knowledge, then having a blocked time in your schedule for reading and thinking is critical.

Your Personal Knowledge Management tool gets more valuable as more knowledge is stored in it. Having the habits and consistency to add more information into this tool will give you exponential returns over time.

#productivity

I recently watched the excellent documentary The Social Dilemma on Netflix which talks about the rise of social media and how it influences our behavior and damages our society.

Social media today is a triple-whammy of forces. First, like any other business, the platform itself is trying to grow. This means getting more users and monetize them through advertising. Second, to get more and more users, the platform has to make users interact with each other and spend more time on the platform. They achieve this by incentivizing users to seek attention. You get attention not just when your online behavior is positive (e.g. funny and catchy) but also when it's negative (e.g. controversial and shocking). Third, social media platforms want to make advertisers happy because advertisers give them money. Advertisers want to change your behavior, which can range anywhere from the mundane (e.g. buying product) to nefarious (e.g. changing your vote — as entertainingly explained by another Netflix documentary, The Great Hack).

The intent and principles of those three things are not new. Pretty much all businesses want to grow and want to get you to use more of their products. Many businesses also get revenue from putting advertising on their properties. The difference is that today, technology has made the scale and impact of change humongous. There are more than 2 billion users on Facebook-owned social media platforms, and Facebook has detail data about each one. It has been proven time and again that Big Data and Artificial Intelligence can successfully change users' behaviors. Furthermore, social media platforms try to change our behavior surreptitiously. I think this is why our society has such a blind spot with this issue.

The impact on mental health is real. The documentary points out the increase in suicide rates among teenagers. But I'm sure the impact is not only for the young ones. For teenagers on Instagram, it may be self-consciousness about body imperfection. For professionals on LinkedIn, it may be comparing career achievements with others.

Are there solutions to this issue? The root cause is the business model of social media platforms and how this industry is currently unregulated. As long as we (as a society) prefer “free” content with ads, we will continue to have this issue.

The documentary itself proposes a solution for people to delete their social media accounts. However, I think there is still a way to gain the benefits from social media without being negatively influenced by it. My own approach is to be a stoic and use social media mindfully and purposefully. I use social media mainly as contact tools, i.e. for networking and keeping in touch. LinkedIn and Facebook are great for this purpose. I set guidelines so they continue to be useful. For example, here's how I engage with marketers on LinkedIn. I also impose limits on myself. Once I detect that my emotions get affected by my news feed — either positively or negatively — I step away and close my browser.

In the end, how each of us uses social media depends on our own comfort level. Do, however, proceed with your eyes open. “The Social Dilemma” is one entertaining way to be informed about this subject. Another good resource is Ten Arguments For Deleting Your Social Media Accounts Right Now.

#productivity

#bookreviews