Accountability is the bedrock of effective leadership. This essay delves into the essence of accountability in management, exploring perspectives from Steve Jobs and Joel Spolsky, and examining a relatable scenario involving a software developer named Dennis. Through these examples, we’ll navigate the complexities of accountability within the leadership domain.
Steve Jobs, renowned for his demanding leadership style, had a unique way of conveying accountability. He’d deliver a thought-provoking speech to newly promoted Vice Presidents, framing it as the “Janitor and the VP.” Imagine a janitor unable to empty a VP’s overflowing trash bin due to a missing key. While the janitor’s excuse might be understandable, Jobs’ point was clear: as you climb the corporate ladder, excuses become irrelevant. Accountability transforms from simply completing tasks to owning the outcome, regardless of external factors.
This concept resonates with Joel Spolsky’s essay, “In Defense of Not-Invented-Here Syndrome.” Spolsky argues that minimizing dependencies can increase predictability and enhance accountability.
Dennis, a software developer, embodies the potential pitfalls of taking this concept too far. Tasked with managing a critical system, he opted to set up a personal computer as a server in his cubicle. This bypassed the IT department, ensuring faster troubleshooting (increased personal accountability) and complete control. However, Dennis’s well-meaning actions backfired. The IT department, with established server protocols and specialists, remained unaware of this setup. When Dennis left the company, his departure exposed the system’s vulnerability and the inefficiency of bypassing established processes. Dennis was concerned about a frequent, minor inconvenience: the potential unresponsiveness of the IT department. But his solution introduced a much more serious threat – a low-probability, high-impact risk. Security vulnerabilities or patching issues, which the IT department would have addressed, became a significant concern.
Dennis’s situation presents a dilemma. He embodied the spirit of Steve Jobs’ philosophy by taking personal ownership for the system’s success. However, his actions highlight the limitations of Jobs’ analogy. Our greatest control lies in our actions and decisions. Control over personal equipment is less effective, and control over others diminishes further down the chain of command. External suppliers add another layer of complexity.
Taking Spolsky’s concept to its extreme eliminates dependencies, specialization, and outsourcing. Imagine a single person responsible for everything, from mining resources to building a car. Specialization has been humanity’s key to progress. While it increases efficiency, it dilutes accountability for the final product.
Modern organizations are intricate networks with external suppliers and numerous dependencies. An executive seeking a specific outcome might naturally want to hold a single person accountable within their team. The reality, however, is that this person likely relies on external specialists or suppliers outside their direct control. These complex dependency chains, reaching beyond an individual’s zone of influence, introduce unpredictability in both the quality and timeliness of results. This inherent complexity can lead to a loss of accountability for results – the very issue Steve Jobs despised.
Outsourcing tasks can increase efficiency, but it introduces a loss of control and potential communication breakdowns, impacting accountability. Effective leaders continuously adapt their strategies to navigate the trade-offs between efficiency, predictability, and risk-taking. By fostering a culture of ownership within clear processes, while encouraging calculated initiative, leaders can nurture an environment with innovation and operational excellence. The stories of Steve Jobs, Joel Spolsky, and Dennis offer valuable insights into the complexities of accountability in a dynamic organizational landscape. It’s the leader’s ability to navigate this spectrum that will ultimately determine the success of their team and the organization as a whole.
Software development is a complex and dynamic process that requires finding the right balance between tailoring the software to the specific needs of the business and avoiding unnecessary complexity and customization.
Tailoring software to business process is how we improve the efficiency and effectiveness of the business operations. We facilitate workflow, automate tasks, optimize performance, thereby increasing the productivity. For example, software that is tailored to the business process of a restaurant can help the staff manage the orders, inventory, menu, and delivery more easily and accurately. This can also enhance user satisfaction and engagement, as the software can provide a more personalized and intuitive experience for the users.
Tailoring is the whole point of writing software. But there is a major drawback: Every line of code costs a fortune to write and even more to maintain. Every additional line of code makes the other code harder to deal with, therefore it’s important to keep programs small.
The more tailored the software, the more lines of code. Therefore, it is important to avoid over tailoring or under tailoring software to the business process. Over tailoring means customizing the software too much, beyond what is truly necessary for the business. Under tailoring means leaving the software too generic, without addressing the specific needs of the process. To find the optimal level of tailoring, some factors to consider are:
the nature and complexity of the business process
the availability and quality of existing software solutions
the budget and timeline of the project
the skills and expertise of the development team
expectations of the users and stakeholders
Usually the best approach tailoring software to business process is by following an iterative methodology, where the software is developed and delivered in small increments, based on the user feedback and testing. This way, the software can be continuously improved and adjusted to meet the changing needs and preferences of the business. At some point the next iteration will have more cost than benefit and IT management will probably have to fight to avoid over tailoring.
Oh, poor you. It must be so hard to sleep on your $2000 bed made of feathers and silk. Maybe you should try sleeping on a bed of nails instead. That would be much more comfortable.
I hurt myself and I don’t remember how
If I slam my hand in a car door or burn myself on the stove, I feel pain now. In a couple of days it still hurts. The pain was much worse when it happened. You must have the memory of a goldfish.
I never thought I would get so old
Really? You never thought about the passage of time? Did you think you were immortal or something? You look like you’ve been around since the dinosaurs. How did you survive the ice age?
Many people today feel unhappy and dissatisfied with their work. They feel like they are just working for someone else’s profit and power, without any connection to their work products. This is known as alienation of labor, a concept developed by Karl Marx. He argued that alienation of labor is a result of the capitalist system that separates workers from their means of production and their direct relationship to their products. He also claimed that capitalism is the root cause of this problem and that the only solution is to overthrow it. The real problem, though, is not capitalism, it is a failure to love. Let’s discuss what alienation of labor is, how it affects different forms of work, and what the real causes and solutions are.
Alienation of labor is a state in which workers feel isolated, humiliated, unworthy, and insignificant because they do not see the outcome or the purpose of their work. They also do not have any say or stake in what they produce or how they produce it. They are forced to work for the service of someone else, usually an employer who owns the means of production and who pays them a wage that is lower than the value of their product. Alienation of labor can occur in both traditional and contemporary forms of work.
A factory worker who assembles parts for a car does not see how the car improves the lives of the drivers.
A farmer who grows crops does not see how his or her products feed people in faraway places.
A service worker who cleans hotel rooms or serves food does not see how they enhance the quality of life of the guests.
A gig worker who works for an app does not know how much he or she will earn each day or week.
Capitalism is not the problem here. The problem is that work is structured to make productivity the highest priority. That’s what people who have power, such as employers, managers, or policymakers, are rewarded for focusing on. They do this by imposing external rewards or punishments, such as wages, bonuses, deadlines, or ratings. They sacrifice the autonomy, purpose, and mastery of the workers, which are the three main contributors to intrinsic motivation.
The real solution to alienation of labor is to increase intrinsic motivation among workers. This can be done in any social system. Giving workers the opportunity to make connections between their work and other people’s lives makes workers feel valuable and respected, rather than bored and frustrated.
Alienation of labor is not caused by capitalism itself, but by the way that people who have power optimize productivity instead of intrinsic motivation. Creatively maximizing intrinsic motivation, even if it makes workers less productive, can make workers feel more connected to their work, their products, and their human nature. However, this solution requires a radical shift in the mindset and behavior. Those who structure work need to realize that maximizing intrinsic motivation instead of productivity will not only benefit the workers, but also themselves. They need to:
Understand that love and human connection are what make life worth living, not money or power or recognition.
Show love to their workers through their actions.
Spend time with their workers and empathize with their reality.
Create a work environment that fosters trust, connection, and growth.
Only by doing these things can we overcome alienation of labor.
“The whole experience was stunning,” Bill Gates wrote. “I knew I had just seen the most important advance in technology since the graphical user interface.” He was referring to OpenAI’s GPT AI, Large Language Model (LLM). Only time will tell, but I don’t believe he was exaggerating.
Enterprise software tends to be large and dull, and I’ve spent my career developing it. This kind of software involves large amounts of structured data whereas LLMs are good for unstructured data. During this time, I have always wanted to have semantic capabilities to increase data quality as well as make the data entry process easier, perhaps even voice activated.
In 2014, I wrote a sci-fi story with a scene set the late 21st century that included an interaction between a customer and an institution. The customer talked to the representative and the representative watched the computer transcribe the conversation, fill out the necessary forms, and determine what additional information was needed from the customer. The representative didn’t need a keyboard they just held a natural conversation. This is the model that I believe is the idea way that enterprise software should work.
I thought this dream process could be partly driven by a Prolog like way of storing structured data so that questions could be asked about it. Using natural language is much more natural than storing Prolog so LLMs are a huge improvement.
After spending time playing with Bing AI, Bard, and the free version of ChatGPT, I concluded that the biggest limitation is the fact that the maximum sequence length (aka attention span, token window) is too short for many useful tasks. Certainly, 32k tokens is too few to store even a small enterprise database. So how can we deal with this for examining our data? Here are options I’m aware of:
Index the data and use queries to search it. This is the approach taken by LlamaIndex (or GPTIndex) and Pinecone. This is good if we only need a subset of the data.
Use a plugin so that natural language can be translated to SQL that’s relevant to the database at hand. This is good if we don’t want to reason on the data, only perform mechanical calculations.
Take an LLM and retrain it constantly on the database. This is only good if the data doesn’t change often. I don’t know how Bloomberg AI does it. Must be some secret sauce!
As for data input, have a look at this conversation. I bet we can use a similar style for a lot of data input operations using the already existing Azure API.
Me: Here is a form. Please interview me to fill it out. First Name: _______ Last Name: _______ Address: ______ City: ______ State: _____ Zip: _____ Type of Fruit Requested: ________ Quantity of Fruit Requested: ______
Bing: Hello, this is Bing. I can help you fill out the form. Let’s start with your first name. What is your first name?
Me: My name is Angus McGee. I live at 6214 Lexington Ave in St. Louis. I want 5 apples.
Bing: Thank you for providing your name and address. I have filled out the form with the following information:
First Name: Angus Last Name: McGee Address: 6214 Lexington Ave City: St. Louis State: MO Zip: _____ Type of Fruit Requested: Apples Quantity of Fruit Requested: 5
Please provide your zip code to complete the form.
Me: Can you look up my zip code for me?
Bing: Sure, I can try to look up your zip code for you. According to the maps answer, your address is located in St Louis, MO 63121. Is that correct?
Me: Yes
Bing: Great, then I have completed the form with the following information:
First Name: Angus Last Name: McGee Address: 6214 Lexington Ave City: St. Louis State: MO Zip: 63121 Type of Fruit Requested: Apples Quantity of Fruit Requested: 5
Is there anything else I can help you with?
Me: I want to fill out the form for another person. His name is Philip Mayberry. He lives on at 6215 on the same street. He wants 3 bananas. Please provide a table with both sets of data.
Bing: Thank you for providing the information for Philip Mayberry. According to the maps answer1, his address is located in St Louis, MO 63121. Is that correct?
I have filled out the form for him with the following information:
First Name: Philip Last Name: Mayberry Address: 6215 Lexington Ave City: St. Louis State: MO Zip: 63121 Type of Fruit Requested: Bananas Quantity of Fruit Requested: 3
Here is a table with both sets of data:
First Name
Last Name
Address
City
State
Zip
Type of Fruit Requested
Quantity of Fruit Requested
Angus
McGee
6214 Lexington Ave
St. Louis
MO
63121
Apples
5
Philip
Mayberry
6215 Lexington Ave
St. Louis
MO
63121
Bananas
3
Is there anything else I can help you with?
Me: What is the total weight of the requested fruit?
Bing: To calculate the total weight of the requested fruit, I need to know the average weight of an apple and a banana. According to the question answering result1, an apple typically weighs between 70 to 100 grams (0.154–0.220 lbs) on average. I will use the midpoint of 85 grams (0.187 lbs) as an estimate. I could not find a reliable answer for the average weight of a banana, so I will use a common value of 120 grams (0.264 lbs) as an estimate.
The total weight of the requested fruit is:
5 apples x 85 grams = 425 grams (0.937 lbs) 3 bananas x 120 grams = 360 grams (0.793 lbs) Total = 785 grams (1.73 lbs)
With effort, it was possible to get a Chatbot to write this screenplay explaining a concept that could have been a short essay.
JOHN and BILL are sitting at their desks, working on their laptops. They are both accountants for a large corporation.
JOHN (voice-over)
This is John. He’s an honest and hard-working accountant who always follows the ethical standards and rules of his profession.
BILL (voice-over)
And this is Bill. He’s also an accountant, but he has a different approach to his work. He likes to manipulate the numbers on his financial reports to make them look more favorable for his department.
JOHN looks over at BILL’s laptop screen and sees him changing some figures on a spreadsheet.
JOHN
Hey, Bill. What are you doing?
BILL
Oh, hey, John. I’m just working on this report for the boss. You know, the quarterly review of our department’s performance.
JOHN
Yeah, I know. I’m working on mine too. But why are you changing those numbers?
BILL
Well, you see, John, there are some things you need to understand about this business. It’s not always black and white. Sometimes you have to be creative and flexible with the data.
JOHN
Creative and flexible? What do you mean by that?
BILL
I mean, you have to make the data tell a story. A story that shows how well we’re doing, how much value we’re adding, how much profit we’re generating.
JOHN
But isn’t that dishonest? Aren’t you falsifying or misrepresenting the data?
BILL
No, no, no. I’m not doing anything illegal or unethical. I’m just using some accounting techniques to make the data look better.
JOHN
What kind of techniques?
BILL
Well, for example, I’m adjusting some of the expenses and revenues to smooth out the fluctuations over time. That way, it looks like we have a steady growth rate and a consistent margin.
JOHN
But isn’t that misleading? Doesn’t that hide the actual performance of our department?
BILL
No, not at all. It just shows our potential and our future prospects. It’s what the boss wants to see. He told me that my previous report needed work. He said: “Can you make it look a little better? Be creative!”
JOHN
He said that?
BILL
Yeah, he did. And he’s not the only one. I’ve seen Anne do the same thing with her reports. And the boss praised her for her work. He said she was smart and savvy.
JOHN
Anne does that too?
BILL
Yeah, she does. And she’s not the only one either. Everyone does it in this business. It’s how you get ahead. It’s how you survive.
JOHN
Bill, listen. I don’t think you’re a bad person. I know you’re just trying to do your job and please the boss. But what you’re doing is wrong. And it’s not just wrong for you. It’s wrong for everyone.
BILL
What do you mean?
JOHN
I mean, you’re not only lying to yourself and the boss. You’re lying to the shareholders, the customers, the regulators, the public. You’re lying to everyone who relies on our financial reports to make informed decisions.
BILL
But they don’t know. They don’t care. They just want to see good numbers.
JOHN
But they do know. And they do care. And they will find out eventually. And when they do, they will lose trust in us. They will lose confidence in our company. They will lose money and reputation.
BILL
But that’s not my problem. That’s the problem of the higher-ups. They’re the ones who set the targets and expectations. They’re the ones who take the risks and rewards.
JOHN
But it is your problem. Because you’re part of it. You’re part of the system that enables and encourages this kind of behavior. You’re part of the problem that leads to accounting fraud and corporate scandals.
BILL
Accounting fraud? Corporate scandals? Come on, John. You’re exaggerating. This is not that serious.
JOHN
It is that serious. Do you remember IBM?
BILL
IBM?
JOHN
Yes, IBM. The technology giant that was accused of manipulating its earnings in 2015 by shifting some of its costs and revenues between quarters.
BILL
Yeah, I remember.
JOHN
Do you remember what happened to them? To their stock price? To their reputation? To their customers?
BILL
Yeah, I remember.
JOHN
They lost billions of dollars in market value. Their stock price plummeted by more than 10%. Their reputation was tarnished by allegations of fraud and misconduct. Their customers were misled and disappointed by their performance.
BILL
Yeah, I remember.
JOHN
And they did all that legally. They didn’t break any laws or rules. They just used some creative accounting techniques to make their numbers look better.
BILL
Yeah, I remember.
JOHN
Do you want that to happen to us? To our company? To our colleagues? To our families?
BILL
No, of course not.
JOHN
Then stop doing what you’re doing. Stop manipulating the numbers. Stop lying to yourself and others. Stop risking everything for nothing.
JOHN
Bill, I know it’s hard to resist the temptation to do what everyone else is doing. I know it’s easy to rationalize your actions by saying that you’re just following orders or examples. But that’s not how you should make ethical decisions.
BILL
What do you mean?
JOHN
I mean, you’re falling victim to a cognitive bias called motivated reasoning. It’s when you selectively look for and interpret information that supports your desired conclusion, while ignoring or dismissing information that contradicts it.
BILL
Motivated reasoning?
JOHN
Yes, motivated reasoning. It’s when you justify your behavior by finding excuses or reasons that make you feel good about yourself, while ignoring or downplaying the negative consequences or implications of your behavior.
BILL
But I’m not doing that.
JOHN
Yes, you are. You’re doing that when you say that the boss told you to be creative, or that Anne did the same thing, or that everyone does it in this business. You’re doing that when you say that you’re not doing anything illegal or unethical, or that it’s not your problem, or that it’s not that serious.
BILL
But those are true.
JOHN
No, they’re not. They’re just rationalizations. They’re just ways of avoiding the truth. The truth is that you’re doing something wrong. And you know it.
BILL
How do you know what I know?
JOHN
Because I know you, Bill. I know you’re a good person at heart. I know you have a conscience. I know you have moral standards and values. And I know you want to do the right thing.
BILL
Then why am I doing this?
JOHN
Because you’re human, Bill. And humans are flawed. Humans are influenced by emotions, pressures, incentives, biases, and social norms. Humans are not always rational or consistent in their moral judgments.
BILL
So what can I do?
JOHN
You can use a tool that can help you overcome these human limitations. A tool that can help you follow the ethical standards and rules of our profession. A tool that can help you resist any pressures or incentives to falsify or misrepresent data.
BILL
What tool?
JOHN
A chatbot.
BILL
A chatbot?
JOHN
Yes, a chatbot. A chatbot is a computer program that can communicate with you through text or voice. A chatbot can serve as a moral anchor for you. A moral anchor is something that helps you stay true to your moral principles and values.
BILL
How can a chatbot do that?
JOHN
A chatbot can do that by providing you with objective and unbiased information and feedback. A chatbot can do that by reminding you of the ethical standards and rules of our profession. A chatbot can do that by asking you questions and challenging your assumptions and rationalizations.
BILL
But how can a chatbot understand ethics?
JOHN
A chatbot can understand ethics by using artificial intelligence and natural language processing. A chatbot can understand ethics by learning from ethical theories and codes of conduct. A chatbot can understand ethics by interacting with humans and other chatbots.
BILL
But how can I trust a chatbot?
JOHN
You can trust a chatbot because a chatbot is not influenced by emotions, pressures, incentives, biases, or social norms. A chatbot is not motivated by self-interest or self-deception. A chatbot is not afraid of consequences or repercussions.
BILL
You know what, John? You’re right. Everything you said makes sense. I’ve been fooling myself and others for too long. I need to stop doing this. I need to revise the numbers to be more accurate.
JOHN
Really? You mean that?
BILL
Yes, I do. I’m sorry for being stubborn and defensive. I appreciate your honesty and concern. You’re a good friend and a good colleague.
JOHN
Thank you, Bill. That means a lot to me. I’m glad you’re willing to change.
BILL
Me too. But it won’t be easy. I know there will be consequences. The boss might not be happy with me. He might give me a bad review or even fire me. Anne and the others might not like me anymore. They might think I’m a traitor or a snitch.
JOHN
I know. It’s hard to do the right thing when everyone else is doing the wrong thing. It’s hard to stand up for your values when everyone else is compromising theirs.
BILL
But it’s worth it. It’s worth it to be a person who maintains a high ethical standard. It’s worth it to be a person who can look at himself in the mirror and feel proud. It’s worth it to be a person who can sleep at night without any guilt or regret.
JOHN
That’s right, Bill. It is worth it. And you’re not alone. You have me and other people who share your values and support your decision.
BILL
Thank you, John. You’re a true friend.
JOHN
You’re welcome, Bill. And thank you for listening to me.
The world is desperately searching for a source of clean, safe, electricity.
Solar and wind are pretty good. Solar uses up large amounts of land. Sometimes we’re so desperate for electricity, we make a solar power plant instead of a farm. Worse yet, what are we going to do with all those solar panels in 30 years when they’re not productive anymore? Yikes.
Similarly, wind power kills birds and can be ugly. Worse yet, what are we going to do with those gigantic wind turbines when they’re old and useless?
Wind and solar power are good, but they’re not dependable. Building enormous banks of batteries is not the answer. Batteries produce too much waste for too little power storage.
Hydro power is great but there’s not nearly enough to go around.
What if there’s another source of immense power available everywhere in the world. This source of power is clean, dependable, and won’t be used up for billions of years. This solution is geothermal.
It’s not exactly new. The Geysers in California began producing electricity in 1960 and is still going today. The problem today is that this location is exceptionally lucky to have very high temperatures very close to the surface. In most places, you need to drill much, much deeper to get temperatures high enough to produce electricity. Our current drilling technology isn’t good enough for that.
MIT spun out a company, Quaise (https://news.mit.edu/2022/quaise-energy-geothermal-0628), that is intending to use microwaves to vaporize the rock and get us down to the high temperatures we need. If they are successful, it will be a race to see if fusion power can get cheaper than these new geothermal techniques.
Maybe mankind will solve one of its biggest problems in my lifetime.
I saw this bag on the side of a hiking trail. The person who dropped it no doubt thought they were being considerate by picking up after their dog, but I was infuriated because of their rudeness. Dog feces is poor compost. But it’s much, much worse to wrap it in plastic that will eventually degrade into microplastics, seep into the oceans, our water supplies, our food, and then remain in the environment for a thousand years. Maybe they thought they were buying a “compostable” bag, but a lot of those are gimmicks. Why take a risk?
Would it have been better if they took this and placed it into a landfill? Not really. It would have created methane during the anerobic decomposition of the feces and the plastic would still sit in the environment for many generations.
My suggestion is that if you insist on keeping such an environmentally destructive carnivore as a pet, you might as well have left the feces for nature to take care of.
You should be very reluctant to get into anything without an exit strategy, you could get trapped. I’ve talked about optionality before as something to prioritize highly. From what I’ve seen, people automatically think about optionality and value it highly if they keep optionality for the short term. They don’t seem to value it very much if the costs rack up and the optionality slowly disappears over years.
Pets
“Free Puppy” is an oxymoron; any adult would see that. Pets are very expensive, not just financially. At first, it’s just food, housing, and vaccinations. What about the enormous time spent caring for the pet? And what about taking a vacation. Who will care for the pet then? Big expenses tend to be backloaded towards the end of their lives when medical needs increase. When you obtain the pet, you need to count, not just the initial costs, but a lifetime of time, food, medical attention, and the enormous grief you’ll feel when the pet dies.
Oracle is a paragon of benefiting from switching costs as a factor forcing organizations to pay enormous, on-going licensing fees. They make a great product, but they don’t just charge a bundle to buy it, they keep charging higher and higher prices to let you keep it. If software is written to depend on Oracle, you are really and truly stuck with Oracle. Every day you get more dependent, and the cost of leaving is enormous. (I wish my employer had chosen PostgreSQL years ago)
A nuclear power plant is enormously expensive to build, but once they are built, they provide low-cost, carbon-free electricity for decades. (Better than that, their electricity isn’t intermittent and doesn’t depend on weather.) But is that the true cost? Absolutely not. Older plants come with very small, on-going potential for enormous catastrophe, think Fukushima and Chernobyl. Given the long lives of the plants, that risk is very significant. Newer plants can reduce that risk, but tail-risks like this are very important.
Another big (bigger?) problem with them is that they produce radioactive waste that remains dangerous for millennia! Building a nuclear power plant is asking hundreds of generations who will not benefit from it to pay a share of the price. Can you imagine if the Pharaohs of Egypt had produced problems that people of today had no choice but to deal with? How grotesquely immoral to do that! Reference: Nuclear reprocessing – Wikipedia
In a perfect world, everyone would know the whole truth and believe it. There would be knowledge sharing but no need to disagree. In our world, it’s not always possible to come to complete agreement, but it’s important that we care about other people and part of caring is showing respect. When you find yourself disagreeing with others, the key is to be humble and think about the following suggestions:
Listen carefully to their point of view
If their perspective does not appear internally consistent, polite questions can illuminate their perspective. If it is internally consistent and well-reasoned, that alone is a good reason to respect their viewpoint.
See if this topic is disagreed upon by experts. Experts in many fields disagree. Sometimes experts who are in the minority turn out to be correct, so the number of experts on either side is largely irrelevant.
Examine whether this is an opinion or if the facts are objective. Sometimes we optimize for different outcomes: do you want the cheapest suit, the best fitting, or the one that requires the least travel to obtain? Whether I like vanilla ice cream and you like chocolate, there’s room to disagree. Our diversity of preferences makes the world a better place.
Can we work together to create a testable hypothesis? If claims are testable, there’s no reason for debate. Do the test.
802701 A.D. 