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.

Recently, I saw an interesting social media post. In an entrepreneurship forum. A blogger asked for help because he/she couldn't find customers. I now suspect that the writer’s occupation is being disrupted by A.I.

Introduction

Artificial Intelligence (A.I.) has been a hot topic since the 1950s. With recent advances in machine learning, A.I. will touch almost every aspect of our lives. This article will discuss A.I. technology and its social and economic implications.

What's AI?

A computer program or machine with A.I. can think and learn. In general, it's a way to make a computer smart. Able to understand and execute complex tasks. Machine learning, NLP, and robotics are common types of A.I.

AI's global impact

AI will change the world, but probably faster than you think. A.I. already affects our daily lives. It improves our decision-making, efficiency, and productivity.

A.I. is transforming our lives and the global economy. It will create new business and job opportunities but eliminate others. Affected workers may face financial hardship.

AI examples:

OpenAI's GPT-3 text-generation

Developers can train, deploy, and manage models on GPT-3. It handles data preparation, model training, deployment, and inference for machine learning workloads. GPT-3 is easy to use for both experienced and new data scientists.

My team conducted an experiment. We needed to generate some blog posts for a website. We hired a blogger on Upwork. OpenAI created a blog post. The A.I.-generated blog post was of higher quality and lower cost.

MidjourneyAI's Art Contests

AI already affects artists. Artists use A.I. to create realistic 3D images and videos for digital art. A.I. is also used to generate new art ideas and methods.

MidjourneyAI and GigapixelAI won a contest last month. It's AI. created a beautiful piece of art that captured the contest's spirit. AI triumphs. It could open future doors.

After the art contest win, I registered to try out these new image generating A.I.s. In the MidjourneyAI chat forum, I noticed an artist's plea. The artist begged others to stop flooding RedBubble with AI-generated art.

Shutterstock and Getty Images have halted user uploads. AI-generated images flooded online marketplaces.

Imagining Videos with Meta

Meta released Make-a-Video this week. It's an A.I. app that creates videos from text. What you type creates a video.

This technology will impact TV, movies, and video games greatly. Imagine a movie or game that's personalized to your tastes. It's closer than you think.

Uses and Abuses of Deepfakes

Deepfake videos are computer-generated images of people. AI creates realistic images and videos of people.

Deepfakes are entertaining but have social implications. Porn introduced deepfakes in 2017. People put famous faces on porn actors and actresses without permission.

Soon, deepfakes were used to show dead actors/actresses or make them look younger. Carrie Fischer was included in films after her death using deepfake technology.

Deepfakes can be used to create fake news or manipulate public opinion, according to an AI.

Voices for Darth Vader and Iceman

James Earl Jones, who voiced Darth Vader, sold his voice rights this week. Aged actor won't be in those movies. Respeecher will use AI to mimic Jones's voice. This technology could change the entertainment industry. One actor can now voice many characters.

AI can generate realistic voice audio from text. Top Gun 2 actor Val Kilmer can't speak for medical reasons. Sonantic created Kilmer's voice from the movie script. This entertaining technology has social implications. It blurs authentic recordings and fake media.

Medical A.I. fights viruses

A team of Chinese scientists used machine learning to predict effective antiviral drugs last year. They started with a large dataset of virus-drug interactions. Researchers combined that with medication and virus information. Finally, they used machine learning to predict effective anti-virus medicines. This technology could solve medical problems.

AI ideas AI-generated Itself

OpenAI's GPT-3 predicted future A.I. uses. Here's what it told me:

AI will affect the economy. Businesses can operate more efficiently and reinvest resources with A.I.-enabled automation. AI can automate customer service tasks, reducing costs and improving satisfaction.

A.I. makes better pricing, inventory, and marketing decisions. AI automates tasks and makes decisions. A.I.-powered robots could help the elderly or disabled. Self-driving cars could reduce accidents.

A.I. predictive analytics can predict stock market or consumer behavior trends and patterns. A.I. also personalizes recommendations. sways. A.I. recommends products and movies. AI can generate new ideas based on data analysis.

Conclusion

A.I. will change business as it becomes more common. It will change how we live and work by creating growth and prosperity.

Exciting times,  but also one which should give us all pause. Technology can be good or evil. We must use new technologies ethically, fairly, and honestly.

“The author generated some sentences in this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication. The text of this post was further edited using HemingWayApp. Many of the images used were generated using A.I. as described in the captions.”

GM Friens

The space had better days. Those greenish spikes...oh wow, haven't felt that in ages. Cryptocurrencies and NFTs have lost popularity. Google agrees. Both are declining.

As seen below, crypto interest spiked in May because of the Luna fall. NFT interest is similar to early October last year.

This makes me think NFTs are mostly hype and FOMO. No art or community. I've seen enough initiatives to know that communities stick around if they're profitable. Once it starts falling, they move on to the next project. The space has no long-term investments. Flip everything.

OpenSea trading volume has stayed steady for months. May's volume is 1.8 million ETH ($3.3 billion).

Despite this, I think NFTs and crypto will stick around. In bad markets, builders gain most.

Only 4k developers are active on Ethereum blockchain. It's low. A great chance for the space enthusiasts.

An employee of OpenSea might get a 40-year prison sentence for insider trading using NFTs.

Nathaniel Chastian, an OpenSea employee, traded on insider knowledge. He'll serve 40 years for that.

Here's what happened if you're unfamiliar.

OpenSea is a secondary NFT marketplace. Their homepage featured remarkable drops. Whatever gets featured there, NFT prices will rise 5x.

Chastian was at OpenSea. He chose forthcoming NFTs for OpenSeas' webpage.

Using anonymous digital currency wallets and OpenSea accounts, he would buy NFTs before promoting them on the homepage, showcase them, and then sell them for at least 25 times the price he paid.

From June through September 2021, this happened. Later caught, fired. He's charged with wire fraud and money laundering, each carrying a 20-year maximum penalty.

Although web3 space is all about decentralization, a step like this is welcomed since it restores faith in the area. We hope to see more similar examples soon.

Here's the press release.

Understanding smart contracts

@cantino.eth has a Twitter thread on smart contracts. Must-read. Also, he appears educated about the space, so follow him.

Japan's startup challenge: 7 reasons

Every day, another Silicon Valley business is bought for a billion dollars, making its founders rich while growing the economy and improving consumers' lives.

Google, Amazon, Twitter, and Medium dominate our daily lives. Tesla automobiles and Moderna Covid vaccinations.

The startup movement started in Silicon Valley, California, but the rest of the world is catching up. Global startup buzz is rising. Except Japan.

644 of CB Insights' 1170 unicorns—successful firms valued at over $1 billion—are US-based. China follows with 302 and India third with 108.

Japan? 6!

1% of US startups succeed. The third-largest economy is tied with small Switzerland for startup success.

Mexico (8), Indonesia (12), and Brazil (12) have more successful startups than Japan (16). South Korea has 16. Yikes! Problem?

Why Don't Startups Exist in Japan More?

Not about money. Japanese firms invest in startups. To invest in startups, big Japanese firms create Silicon Valley offices instead of Tokyo.

Startups aren't the issue either. Local governments are competing to be Japan's Shirikon Tani, providing entrepreneurs financing, office space, and founder visas.

Startup accelerators like Plug and Play in Tokyo, Osaka, and Kyoto, the Startup Hub in Kobe, and Google for Startups are many.

Most of the companies I've encountered in Japan are either local offices of foreign firms aiming to expand into the Japanese market or small businesses offering local services rather than disrupting a staid industry with new ideas.

There must be a reason Japan can develop world-beating giant corporations like Toyota, Nintendo, Shiseido, and Suntory but not inventive startups.

Culture, obviously. Japanese culture excels in teamwork, craftsmanship, and quality, but it hates moving fast, making mistakes, and breaking things.

If you have a brilliant idea in Silicon Valley, quit your job, get money from friends and family, and build a prototype. To fund the business, you approach angel investors and VCs.

Most non-startup folks don't aware that venture capitalists don't want good, profitable enterprises. That's wonderful if you're developing a solid small business to consult, open shops, or make a specialty product. However, you must pay for it or borrow money. Venture capitalists want moon rockets. Silicon Valley is big or bust. Almost 90% will explode and crash. The few successes are remarkable enough to make up for the failures.

Silicon Valley's high-risk, high-reward attitude contrasts with Japan's incrementalism. Japan makes the best automobiles and cleanrooms, but it fails to produce new items that grow the economy.

Changeable? Absolutely. But, what makes huge manufacturing enterprises successful and what makes Japan a safe and comfortable place to live are inextricably connected with the lack of startups.

Barriers to Startup Development in Japan

These are the 7 biggest obstacles to Japanese startup success.

1. Unresponsive Employment Market

While the lifelong employment system in Japan is evolving, the average employee stays at their firm for 12 years (15 years for men at large organizations) compared to 4.3 years in the US. Seniority, not experience or aptitude, determines career routes, making it tough to quit a job to join a startup and then return to corporate work if it fails.

1. Conservative Buyers

Even if your product is buggy and undocumented, US customers will migrate to a cheaper, superior one. Japanese corporations demand perfection from their trusted suppliers and keep with them forever. Startups need income fast, yet product evaluation takes forever.

1. Failure intolerance

Japanese business failures harm lives. Failed forever. It hinders risk-taking. Silicon Valley embraces failure. Build another startup if your first fails. Build a third if that fails. Every setback is viewed as a learning opportunity for success.

4. No Corporate Purchases

Silicon Valley industrial giants will buy fast-growing startups for a lot of money. Many huge firms have stopped developing new goods and instead buy startups after the product is validated.

Japanese companies prefer in-house product development over startup acquisitions. No acquisitions mean no startup investment and no investor reward.

Startup investments can also be monetized through stock market listings. Public stock listings in Japan are risky because the Nikkei was stagnant for 35 years while the S&P rose 14x.

5. Social Unity Above Wealth

In Silicon Valley, everyone wants to be rich. That creates a competitive environment where everyone wants to succeed, but it also promotes fraud and societal problems.

Japan values communal harmony above individual success. Wealthy folks and overachievers are avoided. In Japan, renegades are nearly impossible.

6. Rote Learning Education System

Japanese high school graduates outperform most Americans. Nonetheless, Japanese education is known for its rote memorization. The American system, which fails too many kids, emphasizes creativity to create new products.

1. Immigration.

Immigrants start 55% of successful Silicon Valley firms. Some come for university, some to escape poverty and war, and some are recruited by Silicon Valley startups and stay to start their own.

Japan is difficult for immigrants to start a business due to language barriers, visa restrictions, and social isolation.

How Japan Can Promote Innovation

Patchwork solutions to deep-rooted cultural issues will not work. If customers don't buy things, immigration visas won't aid startups. Startups must have a chance of being acquired for a huge sum to attract investors. If risky startups fail, employees won't join.

Will Japan never have a startup culture?

Once a consensus is reached, Japan changes rapidly. A dwindling population and standard of living may lead to such consensus.

Toyota and Sony were firms with renowned founders who used technology to transform the world. Repeatable.

Silicon Valley is flawed too. Many people struggle due to wealth disparities, job churn and layoffs, and the tremendous ups and downs of the economy caused by stock market fluctuations.

The founders of the 10% successful startups are heroes. The 90% that fail and return to good-paying jobs with benefits are never mentioned.

Silicon Valley startup culture and Japanese corporate culture are opposites. Each have pros and cons. Big Japanese corporations make the most reliable, dependable, high-quality products yet move too slowly. That's good for creating cars, not social networking apps.

Can innovation and success be encouraged without eroding social cohesion? That can motivate software firms to move fast and break things while recognizing the beauty and precision of expert craftsmen? A hybrid culture where Japan can make the world's best and most original items. Hopefully.

Everyone wants a scalable startup.

Innovation helps launch a startup. The secret to a scalable business is growth trials (from 1 to 100).

Growth marketing combines marketing and product development for long-term growth.

Today, I'll explain growth hacking strategies popular startups used to scale.

1/ A Facebook user's social value is proportional to their friends.

Facebook built its user base using content marketing and paid ads. Mark and his investors feared in 2007 when Facebook's growth stalled at 90 million users.

Chamath Palihapitiya was brought in by Mark.

The team tested SEO keywords and MAU chasing. The growth team introduced “people you may know”

This feature reunited long-lost friends and family. Casual users became power users as the retention curve flattened.

Growth Hack Insights: With social network effect the value of your product or platform increases exponentially if you have users you know or can relate with.

2/ Airbnb - Focus on your value propositions

Airbnb nearly failed in 2009. The company's weekly revenue was $200 and they had less than 2 months of runway.

Enter Paul Graham. The team noticed a pattern in 40 listings. Their website's property photos sucked.

Why?

Because these photos were taken with regular smartphones. Users didn't like the first impression.

Graham suggested traveling to New York to rent a camera, meet with property owners, and replace amateur photos with high-resolution ones.

A week later, the team's weekly revenue doubled to $400, indicating they were on track.

Growth Hack Insights: When selling an “online experience” ensure that your value proposition is aesthetic enough for users to enjoy being associated with them.

3/ Zomato - A company's smartphone push ensured growth.

Zomato delivers food. User retention was a challenge for the founders. Indian food customers are notorious for switching brands at the drop of a hat.

Zomato wanted users to order food online and repeat orders throughout the week.

Zomato created an attractive website with “near me” keywords for SEO indexing.

Zomato gambled to increase repeat orders. They only allowed mobile app food orders.

Zomato thought mobile apps were stickier. Product innovations in search/discovery/ordering or marketing campaigns like discounts/in-app notifications/nudges can improve user experience.

Zomato went public in 2021 after users kept ordering food online.

Growth Hack Insights: To improve user retention try to build platforms that build user stickiness. Your product and marketing team will do the rest for them.

4/ Hotmail - Signaling helps build premium users.

Ever sent or received an email or tweet with a sign — sent from iPhone?

Hotmail did it first! One investor suggested Hotmail add a signature to every email.

Overnight, thousands joined the company. Six months later, the company had 1 million users.

When serving an existing customer, improve their social standing. Signaling keeps the top 1%.

5/ Dropbox - Respect loyal customers

Dropbox is a company that puts people over profits. The company prioritized existing users.

Dropbox rewarded loyal users by offering 250 MB of free storage to anyone who referred a friend. The referral hack helped Dropbox get millions of downloads in its first few months.

Growth Hack Insights: Think of ways to improve the social positioning of your end-user when you are serving an existing customer. Signaling goes a long way in attracting the top 1% to stay.

These experiments weren’t hacks. Hundreds of failed experiments and user research drove these experiments. Scaling up experiments is difficult.

Contact me if you want to grow your startup's user base.

Great News about the new Google Business Intelligence Solution

Google has renamed Data Studio to Looker Studio and Looker Studio Pro.

Now, Google releases Looker Studio Pro. Similar to the move from Data Studio to Looker Studio, Looker Studio Pro is basically what Looker was previously, but both solutions will merge. Google says the Pro edition will acquire new enterprise management features, team collaboration capabilities, and SLAs.

In addition to Google's announcements and sales methods, additional features include:

Looker Studio assets can now have organizational ownership. Customers can link Looker Studio to a Google Cloud project and migrate existing assets once. This provides:

• Your users' created Looker Studio assets are all kept in a Google Cloud project.

• When the users who own assets leave your organization, the assets won't be removed.

• Using IAM, you may provide each Looker Studio asset in your company project-level permissions.

• Other Cloud services can access Looker Studio assets that are owned by a Google Cloud project.

Looker Studio Pro clients may now manage report and data source access at scale using team workspaces.

Google announcing these features for the pro version is fascinating. Both products will likely converge, but Google may only release many features in the premium version in the future. Microsoft with Power BI and its free and premium variants already achieves this.

Sources and Further Readings

Google, Release Notes (2022)

Google, Looker (2022)