My closing keynote from Product Camp Poland 2018.
As technologists, we all wield great power. I think we have an ethical responsibility to use this wisely. Alas, most people are confused by terms such as "morals" and "ethics." What is the difference? How can I apply this to my own work?
There are a lot of bullet points. I know this isn't fashionable, but I wanted you to be able to print this out and use it as a reference in your work.
15. • It’s not just “1” and “0”
• Or right and wrong
• Or “yes” and “no”
• Or “black” and “white”
The world is grey and difficult. Learn to live with it.
The world isn’t binary
32. • Asking “loaded” questions
• Manipulating the results
• Hiding the results
• Not actually doing the research
Four problems
33. • Asking “loaded” questions
• Manipulating the results
• Hiding the results
• Not actually doing the research
Four problems
34.
35. 1. Was the product information sufficient and
relevant?
6/10
2. Was the transaction cost of the products
appropriate?
1/10
3. Were you satisfied with the website
experience?
5/10
Interpreting interrelated questions
36. • Asking “loaded” questions
• Manipulating the results
• Hiding the results
• Not actually doing the research
Four problems
37.
38.
39.
40. • Asking “loaded” questions
• Manipulating the results
• Hiding the results
• Not actually doing the research
Four problems
41.
42. • Asking “loaded” questions
• Manipulating the results
• Hiding the results
• Not actually doing the research
Four problems
44. “Return on Investment is based on historic
data. It is a backward-looking metric that
yields no insights into how to improve
business results in the future.”
www.maxi-pedia.com
45. • Examine the research sources
• Ask relevant follow-up questions
• Don’t trust client research. Verify it.
• Watch out for personal or political agendas
• Call bullshit when you see it
What you can do
51. • If you are asked to hide information:
– Ask yourself if this is a valid request
– Make sure whatever you do is in the user’s interest
• If someone unexpectedly complicates your
wireframes and/or sitemap:
– Find out if there is a hidden agenda
– If there is, take an ethical stand to do what’s right
What you can do
57. • Ask yourself if the content is honest
• Ask yourself if this is really in the user’s best
interests
• Ask yourself if this is in the business’s best
interests
• Don’t force content providers to publish
information they cannot provide
• Call bullshit when you see it!
What you can do
59. • Bait-and-switch techniques
– Online casinos
• Peer pressure techniques
– Snapchat, Instagram, Facebook
• Ludomania disguised as entertainment
What to look out for
64. • Sites that trick you to:
– Opt in to something you do not want
– Buy something you do not want
• Sites that require information they are not
entitled to:
– Telephone number
– Personal details (e.g. gender)
What to look out for
65.
66. • People do not read very carefully
• People will often accept that they have been
tricked because it takes too long to put things
right again
Some sad facts
73. • Designs that are “flavour of the month”
– WordPress
– Flat design
• Colleagues who do not meet their obligations
• Clients and employers who are asking you to
bend your personal code of ethics
What to look out for
76. • If you are a manager, give your team members
and opportunity to opt out
• If you are a team member, let your manager
know if the projects makes you uncomfortable
• Respect any NDAs you have signed
• If you make a promise, keep it!
What you can do
80. • So-called UX projects where no one has
actually ever talked to a user
• Fake personas
• Projects where assumptions are given the
same weight as actual research
• Team members who exhibit strong cognitive
bias
• Civil servants and mediocre managers who
just want an impressive report, but do not
actually want to improve UX
What to look out for
81. • Validate your assumptions
• Test your prototypes, apps, and existing sites
with real users
• Mine the existing data for genuine insights
What you can do
84. • Validate your assumptions
• Test your prototypes, apps, and existing sites
with real users
• Mine the existing data for genuine insights
What you can do
86. • Validate your assumptions
• Test your prototypes, apps, and existing sites
with real users
• Mine the existing data for genuine insights
• Check for cultural bias
– Racist, religious, and sexist discrimination
• Train your algorithm with unbiased data
• Monitor your AI bot regularly
What you can do
125. 1. The ship was sailing quite fast
2. The iceberg was very far to the south
3. An ice warning was not relayed to the Captain
4. The calm sea showed no wake from the berg
5. The rudder was too small to turn the ship
6. The rivets became brittle in cold water
7. The watertight bulkheads were not tall enough
8. If the Titanic had hit the berg head on it might
have survived the impact
The Titanic disaster – contributing factors