Many developers do it, but I don't approve.

Aren't many programmers part-time? Many work full-time but also freelance. If the job agreement allows it, I see no problem.

Tech businesses' policies vary. I have a friend in Google, Germany. According to his contract, he couldn't do an outside job. Google owns any code he writes while employed.

I was shocked. Later, I found that different Google regions have different policies.

A corporation can normally establish any agreement before hiring you. They're negotiable. When there's no agreement, state law may apply. In court, law isn't so simple.

I won't delve into legal details. Instead, let’s talk about the incident.

How he was discovered

In one month, he missed two deadlines. His boss was frustrated because the assignment wasn't difficult to miss twice. When a team can't finish work on time, they all earn bad grades.

He annoyed the whole team. One team member (anonymous) told the project manager he worked on side projects during office hours. He may have missed deadlines because of this.

The project manager was furious. He needed evidence. The manager caught him within a week. The manager told higher-ups immediately.

The company wanted to set an example

Management could terminate him and settle the problem. But the company wanted to set an example for those developers who breached the regulation.

Because dismissal isn't enough. Every organization invests heavily in developer hiring. If developers depart or are fired after a few months, the company suffers.

The developer spent 10 months there. The employer sacked him and demanded ten months' pay. Or they'd sue him.

It was illegal and unethical. The youngster paid the fine and left the company quietly to protect his career.

Right or wrong?

Is the developer's behavior acceptable? Let's discuss developer malpractice.

During office hours, may developers work on other projects? If they're bored during office hours, they might not. Check the employment contract or state law.

If there's no employment clause, check country/state law. Because you can't justify breaking the law. Always. Most employers own their employees' work hours unless it's a contractual position.

If the company agrees, it's fine.

I also oppose companies that force developers to work overtime without pay.

Most states and countries have laws that help companies and workers. Law supports employers in this case. If any of the following are true, the company/employer owns the IP under California law.

• using the business's resources

• any equipment, including a laptop used for business.

• company's mobile device.

• offices of the company.

• business time as well. This is crucial. Because this occurred in the instance of my junior.

Company resources are dangerous. Because your company may own the product's IP.  If you have seen the TV show Silicon Valley, you have seen a similar situation there, right?

Conclusion

Simple rule. I avoid big side projects. I work on my laptop on weekends for side projects. I'm safe. But I also know that my company might not be happy with that.

As an employee, I suppose I can. I can make side money. I won't promote it, but I'll respect their time, resources, and task. I also sometimes work extra time to finish my company’s deadlines.

University entrepreneurship is like a Willy Wonka Factory of ideas. Classes, roommates, discussions, and the cafeteria all inspire new ideas. I've seen people establish a business without knowing its roots.

Chicken or egg? On my mind: I've asked university founders around the world whether the problem or solution came first.

The Problem

One African team I met started with the “instant noodles” problem in their academic ecosystem. Many of us have had money issues in college, which may have led to poor nutritional choices.

Many university students in a war-torn country ate quick noodles or pasta for dinner.

Noodles required heat, water, and preparation in the boarding house. Unreliable power from one hot plate per blue moon. What's healthier, easier, and tastier than sodium-filled instant pots?

BOOM. They were fixing that. East African kids need affordable, nutritious food.

This is a real difficulty the founders faced every day with hundreds of comrades.

This sparked their serendipitous entrepreneurial journey and became their business's cornerstone.

The Solution

I asked a UK team about their company idea. They said the solution fascinated them.

The crew was fiddling with social media algorithms. Why are some people more popular? They were studying platforms and social networks, which offered a way for them.

Solving a problem? Yes. Long nights of university research lead them to it. Is this like world hunger? Social media influencers confront this difficulty regularly.

It made me ponder something. Is there a correct response?

In my heart, yes, but in my head…maybe?

I believe you should lead with empathy and embrace the problem, not the solution. Big or small, businesses should solve problems. This should be your focus. This is especially true when building a social company with an audience in mind.

Philosophically, invention and innovation are occasionally accidental. Also not penalized. Think about bugs and the creation of Velcro, or the inception of Teflon. They tackle difficulties we overlook. The route to the problem may look different, but there is a path there.

There's no golden ticket to the Chicken-Egg debate, but I'll keep looking this summer.

10 biases in 10 visuals

Cognitive biases are crucial for UX research, design, and daily life. Our biases distort reality.

After learning about biases at my UX Research bootcamp, I studied Erika Hall's Just Enough Research and used the Nielsen Norman Group's wealth of information. 10 images show my findings.

1. Bias in sampling

Misselection of target population members causes sampling bias. For example, you are building an app to help people with food intolerances log their meals and are targeting adult males (years 20-30), adult females (ages 20-30), and teenage males and females (ages 15-19) with food intolerances. However, a sample of only adult males and teenage females is biased and unrepresentative.

2. Sponsor Disparity

Sponsor bias occurs when a study's findings favor an organization's goals. Beware if X organization promises to drive you to their HQ, compensate you for your time, provide food, beverages, discounts, and warmth. Participants may endeavor to be neutral, but incentives and prizes may bias their evaluations and responses in favor of X organization.

In Just Enough Research, Erika Hall suggests describing the company's aims without naming it.

Third, False-Consensus Bias

False-consensus bias is when a person thinks others think and act the same way. For instance, if a start-up designs an app without researching end users' needs, it could fail since end users may have different wants. https://www.nngroup.com/videos/false-consensus-effect/

Working directly with the end user and employing many research methodologies to improve validity helps lessen this prejudice. When analyzing data, triangulation can boost believability.

Bias of the interviewer

I struggled with this bias during my UX research bootcamp interviews. Interviewing neutrally takes practice and patience. Avoid leading questions that structure the story since the interviewee must interpret them. Nodding or smiling throughout the interview may subconsciously influence the interviewee's responses.

The Curse of Knowledge

The curse of knowledge occurs when someone expects others understand a subject as well as they do. UX research interviews and surveys should reduce this bias because technical language might confuse participants and harm the research. Interviewing participants as though you are new to the topic may help them expand on their replies without being influenced by the researcher's knowledge.

Confirmation Bias

Most prevalent bias. People highlight evidence that supports their ideas and ignore data that doesn't. The echo chamber of social media creates polarization by promoting similar perspectives.

A researcher with confirmation bias may dismiss data that contradicts their research goals. Thus, the research or product may not serve end users.

Design biases

UX Research design bias pertains to study construction and execution. Design bias occurs when data is excluded or magnified based on human aims, assumptions, and preferences.

The Hawthorne Impact

Remember when you behaved differently while the teacher wasn't looking? When you behaved differently without your parents watching? A UX research study's Hawthorne Effect occurs when people modify their behavior because you're watching. To escape judgment, participants may act and speak differently.

To avoid this, researchers should blend into the background and urge subjects to act alone.

The bias against social desire

People want to belong to escape rejection and hatred. Research interviewees may mislead or slant their answers to avoid embarrassment. Researchers should encourage honesty and confidentiality in studies to address this. Observational research may reduce bias better than interviews because participants behave more organically.

Relative Time Bias

Humans tend to appreciate recent experiences more. Consider school. Say you failed a recent exam but did well in the previous 7 exams. Instead, you may vividly recall the last terrible exam outcome.

If a UX researcher relies their conclusions on the most recent findings instead of all the data and results, recency bias might occur.

I hope you liked learning about UX design, research, and real-world biases.

“I think if I had time to do something else, I would be so excited to go after this company right now.”

Sam Altman, CEO of Open AI, recently discussed AI's present and future.

Open AI is important. They're creating the cyberpunk and sci-fi worlds.

They use the most advanced algorithms and data sets.

GPT-3...sound familiar? Open AI built most copyrighting software. Peppertype, Jasper AI, Rytr. If you've used any, you'll be shocked by the quality.

Open AI isn't only GPT-3. They created DallE-2 and Whisper (a speech recognition software released last week).

What will they do next? What's the next great chance?

Sam Altman, CEO of Open AI, recently gave a lecture about the next trillion-dollar AI opportunity.

Who is the organization behind Open AI?

Open AI first. If you know, skip it.

Open AI is one of the earliest private AI startups. Elon Musk, Greg Brockman, and Rebekah Mercer established OpenAI in December 2015.

OpenAI has helped its citizens and AI since its birth.

They have scary-good algorithms.

Their GPT-3 natural language processing program is excellent.

The algorithm's exponential growth is astounding. GPT-2 came out in November 2019. May 2020 brought GPT-3.

Massive computation and datasets improved the technique in just a year. New York Times said GPT-3 could write like a human.

Same for Dall-E. Dall-E 2 was announced in April 2022. Dall-E 2 won a Colorado art contest.

Open AI's algorithms challenge jobs we thought required human innovation.

So what does Sam Altman think?

The Present Situation and AI's Limitations

During the interview, Sam states that we are still at the tip of the iceberg.

So I think so far, we’ve been in the realm where you can do an incredible copywriting business or you can do an education service or whatever. But I don’t think we’ve yet seen the people go after the trillion dollar take on Google.

He's right that AI can't generate net new human knowledge. It can train and synthesize vast amounts of knowledge, but it simply reproduces human work.

“It’s not going to cure cancer. It’s not going to add to the sum total of human scientific knowledge.”

But the key word is yet.

And that is what I think will turn out to be wrong that most surprises the current experts in the field.

Reinforcing his point that massive innovations are yet to come.

But where?

The Next $1 Trillion AI Company

Sam predicts a bio or genomic breakthrough.

There’s been some promising work in genomics, but stuff on a bench top hasn’t really impacted it. I think that’s going to change. And I think this is one of these areas where there will be these new $100 billion to $1 trillion companies started, and those areas are rare.

Avoid human trials since they take time. Bio-materials or simulators are suitable beginning points.

AI may have a breakthrough. DeepMind, an OpenAI competitor, has developed AlphaFold to predict protein 3D structures.

It could change how we see proteins and their function. AlphaFold could provide fresh understanding into how proteins work and diseases originate by revealing their structure. This could lead to Alzheimer's and cancer treatments. AlphaFold could speed up medication development by revealing how proteins interact with medicines.

Deep Mind offered 200 million protein structures for scientists to download (including sustainability, food insecurity, and neglected diseases).

Being in AI for 4+ years, I'm amazed at the progress. We're past the hype cycle, as evidenced by the collapse of AI startups like C3 AI, and have entered a productive phase.

We'll see innovative enterprises that could replace Google and other trillion-dollar companies.

What happens after AI adoption is scary and unpredictable. How will AGI (Artificial General Intelligence) affect us? Highly autonomous systems that exceed humans at valuable work (Open AI)

My guess is that the things that we’ll have to figure out are how we think about fairly distributing wealth, access to AGI systems, which will be the commodity of the realm, and governance, how we collectively decide what they can do, what they don’t do, things like that. And I think figuring out the answer to those questions is going to just be huge. — Sam Altman CEO

What works and what’s just more toxic positivity

Just keep at it; you’ll get it.

I closed the Zoom call and immediately dropped my head. Open tabs included material on inspiration, burnout, and recovery.

I searched everywhere for ways to avoid burnout.

It wasn't that I needed to keep going, change my routine, employ 8D audio playlists, or come up with fresh ideas. I had several ideas and a schedule. I knew what to do.

I wasn't interested. I kept reading, changing my self-care and mental health routines, and writing even though it was tiring.

Since burnout became a psychiatric illness in 2019, thousands have shared their experiences. It's spreading rapidly among writers.

What is the actual key to recovering from burnout?

Every A-list burnout story emphasizes prevention. Other lists provide repackaged self-care tips. More discuss mental health.

It's like the mid-2000s, when pink quotes about bubble baths saturated social media.

The self-care mania cost us all. Self-care is crucial, but utilizing it to address everything didn't work then or now.

How can you recover from burnout?

Time

Are extended breaks actually good for you? Most people need a break every 62 days or so to avoid burnout.

Real-life burnout victims all took breaks. Perhaps not a long hiatus, but breaks nonetheless.

Burnout is slow and gradual. It takes little bits of your motivation and passion at a time. Sometimes it’s so slow that you barely notice or blame it on other things like stress and poor sleep.

Burnout doesn't come overnight; neither will recovery.

I don’t care what anyone else says the cure for burnout is. It has to be time because time is what gave us all burnout in the first place.