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.

After a crazy second half of 2021 and significant trade volumes into 2022, the market for NFT artworks like Bored Ape Yacht Club, CryptoPunks, and Pudgy Penguins has begun a sharp collapse as market downturns hit token values.

DappRadar data shows NFT monthly sales have fallen below $1 billion since June 2021. OpenSea, the world's largest NFT exchange, has seen sales volume decline 75% since May and is trading like July 2021.

Prices of popular non-fungible tokens have also decreased. Bored Ape Yacht Club (BAYC) has witnessed volume and sales drop 63% and 15%, respectively, in the past month.

BeInCrypto analysis shows market decline. May 2022 cryptocurrency marketplace volume was $4 billion, according to a news platform. This is a sharp drop from April's $7.18 billion.

OpenSea, a big marketplace, contributed $2.6 billion, while LooksRare, Magic Eden, and Solanart also contributed.

NFT markets are digital platforms for buying and selling tokens, similar stock trading platforms. Although some of the world's largest exchanges offer NFT wallets, most users store their NFTs on their favorite marketplaces.

In January 2022, overall NFT sales volume was $16.57 billion, with LooksRare contributing $11.1 billion. May 2022's volume was $12.57 less than January, a 75% drop, and June's is expected to be considerably smaller.

A World Based on Utility

Despite declines in NFT trading volumes, not all investors are negative on NFTs. Although there are uncertainties about the sustainability of NFT-based art collections, there are fewer reservations about utility-based tokens and their significance in technology's future.

In June, business CEO Christof Straub said NFTs may help artists monetize unreleased content, resuscitate catalogs, establish deeper fan connections, and make processes more efficient through technology.

We all know NFTs can't be JPEGs. Straub noted that NFT music rights can offer more equitable rewards to musicians.

Music NFTs are here to stay if they have real value, solve real problems, are trusted and lawful, and have fair and sustainable business models.

NFTs can transform numerous industries, including music. Market opinion is shifting towards tokens with more utility than the social media artworks we're used to seeing.

While the major NFT names remain dominant in terms of volume, new utility-based initiatives are emerging as top 20 collections.

Otherdeed, Sorare, and NBA Top Shot are NFT-based games that rank above Bored Ape Yacht Club and Cryptopunks.

Users can switch video NFTs of basketball players in NBA Top Shot. Similar efforts are emerging in the non-fungible landscape.

Sorare shows how NFTs can support a new way of playing fantasy football, where participants buy and swap trading cards to create a 5-player team that wins rewards based on real-life performances.

Sorare raised 579.7 million in one of Europe's largest Series B financing deals in September 2021. Recently, the platform revealed plans to expand into Major League Baseball.

Strong growth indications suggest a promising future for NFTs. The value of art-based collections like BAYC and CryptoPunks may be questioned as markets become diluted by new limited collections, but the potential for NFTs to become intrinsically linked to tangible utility like online gaming, music and art, and even corporate reward schemes shows the industry has a bright future.

New standards help NFTs reach their full potential.

NFTs lack interoperability and functionality. They have great potential but are mostly speculative. To maximize NFTs, we need flexible smart contracts.

Current requirements are too restrictive.

Most NFTs are based on ERC-721, which makes exchanging them easy. CryptoKitties, a popular online game, used the 2017 standard to demonstrate NFTs' potential.

This simple standard includes a base URI and incremental IDs for tokens. Add the tokenID to the base URI to get the token's metadata.

This let creators collect NFTs. Many NFT projects store metadata on IPFS, a distributed storage network, but others use Google Drive. NFT buyers often don't realize that if the creators delete or move the files, their NFT is just a pointer.

This isn't the standard's biggest issue. There's no way to validate NFT projects.

Creators are one of the most important aspects of art, but nothing is stored on-chain.

ERC-721 contracts only have a name and symbol.

Most of the data on OpenSea's collection pages isn't from the NFT's smart contract. It was added through a platform input field, so it's in the marketplace's database. Other websites may have different NFT information.

In five years, your NFT will be just a name, symbol, and ID.

Your NFT doesn't mention its creators. Although the smart contract has a public key, it doesn't reveal who created it.

The NFT's creators and their reputation are crucial to its value. Think digital fashion and big brands working with well-known designers when more professionals use NFTs. Don't you want them in your NFT?

Would paintings be as valuable if their artists were unknown? Would you believe it's real?

Buying directly from an on-chain artist would reduce scams. Current standards don't allow this data.

Most creator profiles live on centralized marketplaces and could disappear. Current platforms have outpaced underlying standards. The industry's standards are lagging.

For NFTs to grow beyond pointers to a monkey picture file, we may need to use new Web3-based standards.

Introducing NFTs 2.0

Fabian Vogelsteller, creator of ERC-20, developed new web3 standards. He proposed LSP7 Digital Asset and LSP8 Identifiable Digital Asset, also called NFT 2.0.

NFT and token metadata inputs are extendable. Changes to on-chain metadata inputs allow NFTs to evolve. Instead of public keys, the contract can have Universal Profile addresses attached. These profiles show creators' faces and reputations. NFTs can notify asset receivers, automating smart contracts.

LSP7 and LSP8 use ERC725Y. Using a generic data key-value store gives contracts much-needed features:

• The asset can be customized and made to stand out more by allowing for unlimited data attachment.

• Recognizing changes to the metadata

• using a hash reference for metadata rather than a URL reference

This base will allow more metadata customization and upgradeability. These guidelines are:

• Genuine and Verifiable Now, the creation of an NFT by a specific Universal Profile can be confirmed by smart contracts.

• Dynamic NFTs can update Flexible & Updatable Metadata, allowing certain things to evolve over time.

• Protected metadata Now, secure metadata that is readable by smart contracts can be added indefinitely.

• Better NFTS prevent the locking of NFTs by only being sent to Universal Profiles or a smart contract that can interact with them.

Summary

NFTS standards lack standardization and powering features, limiting the industry.

ERC-721 is the most popular NFT standard, but it only represents incremental tokenIDs without metadata or asset representation. No standard sender-receiver interaction or security measures ensure safe asset transfers.

NFT 2.0 refers to the new LSP7-DigitalAsset and LSP8-IdentifiableDigitalAsset standards.

They have new standards for flexible metadata, secure transfers, asset representation, and interactive transfer.

With NFTs 2.0 and Universal Profiles, creators could build on-chain reputations.

NFTs 2.0 could bring the industry's needed innovation if it wants to move beyond trading profile pictures for speculation.

If asked, run.

An entrepreneur asked me about her pitch deck. A Platform as a Service (PaaS).

She told me she hadn't done her 5-year forecasts but would soon.

I said, Don't bother. I added "time-wasting."

“I've been asked”, she said.

“Who asked?”

“a VC”

“5-year forecast?”

“Yes”

“Get another VC. If he asks, it's because he doesn't understand your solution or to waste your time.”

Some VCs are lagging. They're still using steam engines.

10-years ago, 5-year forecasts were requested.

Since then, we've adopted a 3-year plan.

But It's outdated.

Max one year.

What has happened?

Revolutionary technology. NO-CODE.

Revolution's consequences?

Product viability tests are shorter. Hugely. SaaS and PaaS.

Let me explain:

• Building a minimum viable product (MVP) that works only takes a few months.

• 1 to 2 months for practical testing.

• Your company plan can be validated or rejected in 4 months as a consequence.

After validation, you can ask for VC money. Even while a prototype can generate revenue, you may not require any.

Good VCs won't ask for a 3-year business plan in that instance.

One-year, though.

If you want, establish a three-year plan, but realize that the second year will be different.

You may have changed your business model by then.

A VC isn't interested in a three-year business plan because your solution may change.

Your ability to create revenue will be key.

• But also, to pivot.

• They will be interested in your value proposition.

• They will want to know what differentiates you from other competitors and why people will buy your product over another.

• What will interest them is your resilience, your ability to bounce back.

• Not to mention your mindset. The fact that you won’t get discouraged at the slightest setback.

• The grit you have when facing adversity, as challenges will surely mark your journey.

• The authenticity of your approach. They’ll want to know that you’re not just in it for the money, let alone to show off.

• The fact that you put your guts into it and that you are passionate about it. Because entrepreneurship is a leap of faith, a leap into the void.

• They’ll want to make sure you are prepared for it because it’s not going to be a walk in the park.

• They’ll want to know your background and why you got into it.

• They’ll also want to know your family history.

• And what you’re like in real life.

So a 5-year plan…. You can bet they won’t give a damn. Like their first pair of shoes.

An email capturing Steve Jobs's philosophy.

Steve Jobs may have been the most inspired and driven entrepreneur.

He worked on projects because he wanted to leave a legacy.

Steve Jobs' final email to himself encapsulated his philosophy.

After his death from pancreatic cancer in October 2011, Laurene Powell Jobs released the email. He was 56.

Read: Steve Jobs by Walter Isaacson (#BestSeller)

The Email:

September 2010 Steve Jobs email:

“I grow little of the food I eat, and of the little I do grow, I do not breed or perfect the seeds.” “I do not make my own clothing. I speak a language I did not invent or refine,” he continued. “I did not discover the mathematics I use… I am moved by music I did not create myself.”

Jobs ended his email by reflecting on how others created everything he uses.

He wrote:

“When I needed medical attention, I was helpless to help myself survive.”

The Apple co-founder concluded by praising humanity.

“I did not invent the transistor, the microprocessor, object-oriented programming, or most of the technology I work with. I love and admire my species, living and dead, and am totally dependent on them for my life and well-being,” he concluded.

The email was made public as a part of the Steve Jobs Archive, a website that was launched in tribute to his legacy.

Steve Jobs' widow founded the internet archive. Apple CEO Tim Cook and former design leader Jony Ive were prominent guests.

Steve Jobs has always inspired because he shows how even the best can be improved.

High expectations were always there, and they were consistently met.

We miss him because he was one of the few with lifelong enthusiasm and persona.

Most don't understand the issue until it's too late.

My first startup was what entrepreneurs call the hardest. A two-sided marketplace.

Two-sided marketplaces are the hardest startups because founders must solve the chicken or the egg conundrum.

A two-sided marketplace needs suppliers and buyers. Without suppliers, buyers won't come. Without buyers, suppliers won't come. An empty marketplace and a founder striving to gain momentum result.

My first venture made me a struggling founder seeking to achieve traction for a two-sided marketplace. The company failed, and I vowed never to start another like it.

I didn’t. Unfortunately, my second venture was almost as hard. It failed like the second-hardest startup.

What kind of startup is the second-hardest?

The second-hardest startup, which is almost as hard to develop, is rarely discussed in the startup community. Because of this, I predict more founders fail each year trying to develop the second-toughest startup than the hardest.

Fairly, I have no proof. I see many startups, so I have enough of firsthand experience. From what I've seen, for every entrepreneur developing a two-sided marketplace, I'll meet at least 10 building this other challenging startup.

I'll describe a startup I just met with its two co-founders to explain the second hardest sort of startup and why it's so hard. They created a financial literacy software for parents of high schoolers.

The issue appears plausible. Children struggle with money. Parents must teach financial responsibility. Problems?

It's possible.

Buyers and users are different.

Buyer-user mismatch.

The financial literacy app I described above targets parents. The parent doesn't utilize the app. Child is end-user. That may not seem like much, but it makes customer and user acquisition and onboarding difficult for founders.

The difficulty of a buyer-user imbalance

The company developing a product faces a substantial operational burden when the buyer and end customer are different. Consider classic firms where the buyer is the end user to appreciate that responsibility.

Entrepreneurs selling directly to end users must educate them about the product's benefits and use. Each demands a lot of time, effort, and resources.

Imagine selling a financial literacy app where the buyer and user are different. To make the first sale, the entrepreneur must establish all the items I mentioned above. After selling, the entrepreneur must supply a fresh set of resources to teach, educate, or train end-users.

Thus, a startup with a buyer-user mismatch must market, sell, and train two organizations at once, requiring twice the work with the same resources.

The second hardest startup is hard for reasons other than the chicken-or-the-egg conundrum. It takes a lot of creativity and luck to solve the chicken-or-egg conundrum.

The buyer-user mismatch problem cannot be overcome by innovation or luck. Buyer-user mismatches must be solved by force. Simply said, when a product buyer is different from an end-user, founders have a lot more work. If they can't work extra, their companies fail.