The Art of Yielding: How to Lose an Argument and Gain Self-Respect

In the grand arena of human interaction, voices clash and merge, forming a vibrant tapestry of perspectives. It is in these deliberations that people voice their opinions, objections, and counter-arguments, weaving together a rich fabric of collective wisdom. This is normal, as differences in perspectives, when brought together, make for better decisions. However, there is a looming threat that often casts a shadow over these deliberative assemblies—our inability to lose an argument, which poses a risk to democracy and hinders the effectiveness of our communication.

One may argue that falling in love with our own opinions is a natural byproduct of our passion for certain ideas or ideals. Yet, this attachment often blinds us to the possibility of alternative perspectives and can lead us to believe that any rejection of our opinions is a personal affront—a sign of disrespect. The truth is, our opinions and beliefs are not a complete representation of who we are. It is crucial to recognize that we can be respected even when our ideas are not universally accepted.

The trick, then, is not to overinvest in one's own opinion or a particular point. We must learn the wisdom of yielding, of knowing when to let go of our arguments and embrace the insights of others. This does not mean that we should blindly accept every contrary idea that comes our way; rather, it is a matter of acknowledging that our perspective is just one of many.

If you find yourself feeling disrespected when others disagree with you, it is worth examining the root of these emotions. Often, such feelings stem from a place of insecurity or a lack of self-respect. Ironically, the stubborn attachment to our opinions is both a symptom and a cause of these issues. It is a vicious cycle that can only be broken by cultivating a healthy sense of self-respect and a willingness to yield when appropriate.

Indeed, the process of learning how to lose an argument can have profound effects on our self-esteem. When we are able to let go of our need to be right, we open ourselves to the possibility of growth and self-improvement. It is through this willingness to yield that we foster a sense of humility and respect for the ideas of others. Ultimately, it is not about winning or losing the argument; it is about embracing the diversity of perspectives that enrich our collective wisdom.

So, the next time you find yourself in a heated debate, remember to practice the art of yielding. You may just find that, in losing an argument, you gain a deeper sense of self-respect and a renewed appreciation for the complexity of human thought.

The art of rich prompting in writing with AI

In the brave new world of AI-assisted writing, or "wraiting," mastering the art of crafting rich prompts is the key to unlocking engaging, thought-provoking content. Rich prompts set the stage with originality, supporting elements, connectivity, detail, and a clear objective. To excel at creating these powerful prompts, one must commit to practice, experimentation, and continuous refinement.

The world of AI-generated content can be a wild ride, offering profound insights that leave us in awe or underwhelming results that disappoint. Embracing the unpredictability of AI-generated content and adjusting our expectations accordingly is essential to harnessing AI's full potential as a writing partner while preserving our individuality as writers.

Let's dive into two prompts—one poor and one rich—within the realm of philosophy:

Poor prompt: "Write about dialogue and relation."

Rich prompt: "Turn this into a part of a scholarly book chapter. Provide supporting arguments and examples. Do not use subheadings: The ontological understanding of dialogue (Buber) is both powerful and limited. Powerful because it focuses on relations rather than entities or actions. Limited because dialogue is not culturally universal and excludes people with disabilities. Relation is a better category for educational philosophy than dialogue."

Try both, especially if you have access to GPT-4, and appreciate the difference. The poor prompt is vague and generic, while the rich prompt has enough original thought and instructions to invite a nuanced, in-depth exploration of a specific aspect of existentialism, providing context and direction for the AI to generate meaningful content.

When AI-generated content falls short of our expectations, this may indicate one of two things: one is that your prompt is too poor, and another is that you've stumbled upon a unique idea. AI does not understand unique ideas well because it has not encountered them before. Take this opportunity to engage in old-fashioned original writing and then reintroduce AI into the mix to enhance your work with its vast knowledge and pattern recognition capabilities.

In other words, wraiting still involves thinking and generating ideas. All it does is turn compressed, rough ideas into more comprehensible text output. Many people, but not all, start their process by jotting down on paper the initial thoughts, brief arguments, and short thesis statements. This is the most exciting part of brainstorming. Turning it into a coherent text is not necessarily the most rewarding part of the writing process, so we should use AI to assist with that. The synergy between human creativity and artificial intelligence promises to lead us to new intellectual heights.

Anti-CRT is anti-Christian

According to ABC News, at least 35 states have passed or considered legislation on race education1. A total of 16 states have signed into law bills restricting education on race in classrooms or state agencies. There are currently 19 states that are considering bills or policies that restrict race education in schools or state agencies.

According to Brookings, opponents fear that CRT admonishes all white people for being oppressors while classifying all Black people as hopelessly oppressed victims. These fears have spurred school boards and state legislatures from Tennessee to Idaho to ban teachings about racism in classrooms. The legislations mostly ban the discussion, training, and/or orientation that the U.S. is inherently racist as well as any discussions about conscious and unconscious bias, privilege.

Let me put aside the fact that those claims misrepresent CRT. For a more accurate description, read Stanford Encyclopedia of Philosophy. My argument is the incongruity between the anti-Critical Race Theory movement and Christian values. Emphasizing humility and repentance, Christianity encourages self-reflection and acknowledges the inherent imperfections of humanity. Contrarily, the anti-CRT movement tends to propagate a flawless portrayal of American history, which is fundamentally at odds with the Christian belief system.

Pride, considered one of the deadliest sins, is evident in the anti-CRT assertion that America is exceptional and unparalleled. In contrast, CRT is a structuralist approach that examines the deep-seated, systemic roots of racism and other biases. This perspective aligns with the Christian notion of original sin, which posits that humans are innately, profoundly flawed beings.

To clarify, this is not an endorsement of CRT as a flawless theory; it possesses both strengths and weaknesses. Instead, this critique aims to illuminate the inherent contradictions within the anti-CRT movement, specifically regarding its purported Christian values. Many anti-CRT proponents identify as Christians, but the discord between these two belief systems necessitates a choice. To maintain intellectual and spiritual integrity, one must either embrace Christianity or champion the anti-CRT cause, as the two are incompatible. I am not saying CRT is Christian. But anti-CRT is anti-Christian for sure. 

A billion dollars idea: Learning Workflows and Item Response Theory

Quality control is a vital aspect of many business processes, from financial transactions to procurement. In larger organizations, however, the need for multiple reviewers can lead to time-consuming bureaucracy and a drain on resources. But what if we could revolutionize these processes using learning workflows and item response theory?

An example: One common process that requires multiple approvals for quality control is the expense reimbursement process within an organization. Employees often incur various expenses while performing their job duties, such as travel, meals, and office supplies. To ensure accurate and fair reimbursement, the organization typically implements a multi-step approval process.

1. Expense submission: The employee gathers all necessary receipts and documentation and submits an expense report, detailing the nature and amount of each expenditure.
2. Managerial approval: The employee's direct manager reviews the submitted expense report to verify that the expenses are legitimate, reasonable, and in line with company policy. The manager may ask for additional information or clarification if needed before approving the report.
3. Finance department review: After managerial approval, the expense report is sent to the finance department. The finance team checks the report for compliance with company policies, budgetary constraints, and tax regulations. They also ensure the accuracy of the expense categorization and proper documentation.
4. Final approval and reimbursement: Upon the finance department's approval, the expense report is processed for reimbursement. The employee receives the approved reimbursement amount.

In this example, the multi-step approval process is designed to maintain quality control and ensure that all expense reimbursements are accurate, reasonable, and compliant with the organization’s and governmental policies and regulations.

Learning workflows would differentiate between users based on their performance, allowing those who consistently excel to gain a "master-user" status. You just need to treat every form submission as a test, and keep the record for each employee. This approach would ensure that quality control efforts are focused on those who need it most, saving time and resources while maintaining high standards.

Item response theory (IRT) is a statistical framework used in test development to analyze and model the relationship between an individual's latent ability (e.g., proficiency in a subject) and their probability of responding correctly to test items (e.g., questions). IRT is widely used in educational testing and psychometric research to design and evaluate assessments, ensuring they are reliable, valid, and fair. In IRT, each test item is characterized by a set of parameters, which provide information about the item's difficulty, discrimination, and guessing. These parameters help in understanding how well an item can differentiate between individuals with different levels of ability. It assumes that if you can answer a more difficult test question, you are very likely to answer the easier ones.

Applying IRT (Rasch modeling, to be more specific) to business processes means treating each form submission as a test, incentivizing employees to be more careful with their work. Consistently high performance could lead to master-user status, reducing the need for managers to spend time reviewing numerous forms and requests. Of course, master-users should be paid more, for they cost less to oversee.

This combination of smart workflows and item response theory offers a significant business opportunity. Developing an algorithm that transforms every workflow into a learning system could revolutionize the way organizations operate. As users become more competent and achieve master-user status, the algorithm would automatically streamline processes, freeing up more resources and reducing bureaucracy.

If you want to be the next billionaire and understand organization theory, go for it. Thank me when you make it big.

Carry-Forwards and Smart Cuts

Universities are often struggling financially, dreading budget cuts and facing difficult decisions. Yet, at the same time, they often have significant carry-forward - unspent money from one budget year that gets moved into the next. How can this be? This is especially true for academic affairs – the sum of all colleges – that have to explain other units why they keep all these money, but want all others to take on larger cuts.

Take the CSU system, for example. For the next fiscal year (which starts on July 1), it estimates having $2.5 billion in total core reserves, with $714 million in uncommitted funds. While this may seem like a substantial amount, it's crucial to have a financial safety net and development agenda in place when dealing with multiple priorities and navigating the intricacies of higher education funding.

There are three major reasons for carry-forward in university budgets:

1. The Multicolored Budget: University budgets are complex, with different types of money and spending restrictions. Picture a rainbow, where each color represents a different type of funding. A LOT of carry-forward money is restricted, with only specific ways of spending it. Not all money can be spent instantly due to multi-year commitments. In other words, if we promise a newly hired faculty members certain startup funds for two years, we need to make sure the money is there. And then, there are emergencies – some of them may not be seen by others by emergencies, but sometimes we have to react to changing circumstances with a quick program or an event.
2. Investing in the Future: To thrive, a university needs to focus on more than just maintaining its current state. It must invest in development, which requires accumulating funds. Carry-forward money allows universities to support new projects, research, and initiatives that will help them grow and evolve. The paradox here is that in order to invest in the future, universities must save money today.
3. The disproportional impact of small cuts: Operating Expense (OE) budgets for university's academic units, which tend to be the largest chunk of the budget, usually account for below 5% of the total. 95% or more is in personnel, salaries and benefits. Cutting from personnel is difficult, because we rarely lay off staff. Furloughs are incredibly demotivating and frustrating. So the small cut for the overall budget is actually a huge cut that tend to fall on operating expenses. That's why universities need decentralized reserves, like carry-forward, to maintain stability and keep their promises. By having a sizable carry-forward, academic units can respond to challenges without causing chaos in their operations.

A simple question, like “how much money do we have?” is actually not easy to answer. We always have some kind of money but are short on other kinds of money. We have reserves but cannot spend them. This is not to say that here is how it is supposed to be. I cannot say we figure it out perfectly: there are plenty of inefficiencies and candidates for cost reductions. They are just very hard to implement when state cuts its subsidy. Ideally, a university must engage in smart cuts, which include slow, non-disruptive quest to increase revenues and reduce expenses. Instead, we tend to wait till the next budget crisis and implement dumb cuts instead – hiring freezes, travel bans, cutting student support programs, layouts and furloughs. The dumb cuts do not teach us (the organization) anything. As soon as the budget improves, we go right back to where we were. Smart cuts are slow, more gradual, less disruptive, but more consequential. And of course, the focus should be not on cuts, but on growth, on extending into other markets. But I have written about it already.

We are not as complex as we'd like to think

Stephen Wolfram says tha AI demonstrated: “that human language (and the patterns of thinking behind it) are somehow simpler and more “law like” in their structure than we thought.” His observation is both insightful and thought-provoking. The advent of advanced AI, like ChatGPT, has exposed the limitations of human intellect and language. Our initial encounters with such artificial intellect can be both disturbing and humbling, not because the AI is exceedingly intelligent, but because we, as humans, may not be as exceptional as we once believed.

For centuries, humans have marveled at their own intellect and linguistic abilities, often attributing these capabilities to divine origins. This self-amazement led to the concept of being created in the image of a deity. However, over recent decades, zoologists and zoo-psychologists have been gradually dismantling this grandiose self-image by demonstrating that animals share many traits and abilities with humans.

For instance, chimpanzees exhibit tool usage, problem-solving skills, and even rudimentary communication through gestures and vocalizations. Similarly, dolphins have been observed to possess complex social structures and use unique signature whistles to communicate with one another, while African Grey parrots can mimic human speech and understand a variety of words and phrases.

Now, it is the turn of software engineers to further deflate our pride. The ability to generate language, once considered a unique and sophisticated human trait, is now being replicated by AI algorithms like ChatGPT. This demonstrates that our linguistic prowess is not as mysterious or complex as we once thought. In fact, we often recycle and rephrase what we've heard or read before, which diminishes the perceived essence of our humanity.

This realization, although humbling, can lead to a healthier perspective on our place in the world. The true essence of humanity may be smaller than we initially believed, possibly encompassing higher-level creative thinking and advanced ethical reasoning. These are attributes that, so far, neither animals nor machines have been able to fully replicate.

As we come to terms with the diminishing divide between humans, animals, and machines, it may be time to shift our focus from trying to prove our uniqueness to embracing our similarities. By recognizing that we share many traits and abilities with other beings, we can foster a greater sense of empathy and understanding, ultimately benefiting both our own species and the world around us.