The document discusses the potential impact of AI on the design field, highlighting differing perspectives among industry professionals regarding its long-term effects on jobs and creative processes. It outlines the establishment of internal policies for safe AI usage, risks, training, and integrating AI into workflows while emphasizing the importance of critical engagement with AI tools. Additionally, it covers case studies and future projections for AI's role in design, stressing the need for ethical considerations and maintaining creativity amidst technological advancement.

1. 76%
30%
15%

2. Who are we?
Amanda Stadler
Client Lead
Lisbeth Torp Christensen
Head of Digital Products

3. 1508
We design digital experiences,
loveable brands and sustainable
businesses

4. AI and Design?

8. Job loss Dependency Upskilling

9. We learn how to navigate

10. Company culture is key

11. Question:
How do you envision AI shaping your work and the field of design in the long run?
I think AI could lead to entirely new
ways of designing that we can't even
conceptualize yet
9
I foresee AI tools maturing to a point
where they handle mundane tasks,
letting me focus entirely on creative
problem-solving
8
I believe that AI will fundamentally
reshape the design field, introducing
new roles and making some current
roles obsolete
4
I don't think AI will have more than a
marginal impact on my work or the
broader field of design even in the long
term
1

12. What did we do in
1508 when it hit us?

14. Foundation Value Creation
• SXSW 2023
• Everlearn x2
• AI committee formation
The aha moment
Our internal process

15. Foundation Value Creation
• SXSW 2023
• Everlearn x2
• AI committee formation
• Safe usage & Risk management
• Discuss in internal kick offs
• Paragraph in proposal
The aha moment
Guidelines & Policy
Our internal process

16. Foundation Value Creation
• SXSW 2023
• Everlearn x2
• AI committee formation
• Safe usage & Risk management
• Discuss in internal kick offs
• Paragraph in proposal
The aha moment
Guidelines & Policy
Understanding & Testing
• Understand risks
• Explore opportunities
• Upskilling internally
Our internal process

17. Foundation Value Creation
• SXSW 2023
• Everlearn x2
• AI committee formation
• Safe usage & Risk management
• Discuss in internal kick offs
• Paragraph in proposal
• Ensure everyone has the right
tools to work with (efficient &
safely)
• Reduce technical risks of being
dependent on immature tools
• Generative AI as a natural part of
our internal processes?
• AI Solutions as logic options
integrated in our deliverables?
The aha moment
Guidelines & Policy
Understanding & Testing
AI Implementation
• Understand risks
• Explore opportunities
• Upskilling internally
Our internal process

18. Foundation Value Creation
• SXSW 2023
• Everlearn x2
• AI committee formation
• Safe usage & Risk management
• Discuss in internal kick offs
• Paragraph in proposal
• Ensure everyone has the right
tools to work with (efficient &
safely)
• Reduce technical risks of being
dependent on immature tools
• Generative AI as a natural part of
our internal processes?
• AI Solutions as logic options
integrated in our deliverables?
The aha moment
Guidelines & Policy
Understanding & Testing
AI Implementation
• Understand risks
• Explore opportunities
• Upskilling internally
Our internal process

20. Generative AI exploration is accelerating, thanks to the
popularity of stable diffusion, midjourney, ChatGPT and
large language models. End-user organizations in most
industries aggressively experiment with generative AI.
Gartner VP Analyst Svetlana Sicular,

22. AI Guidelines
Transparency
We are open with our clients
about what tools we use and
when we use it in the process.
Privacy
We respect the privacy of both
our colleagues and clients. We
do not paste or type in any
names of individuals or
company names while using any
AI tools.
AI with clients

23. AI Guidelines
Human decision-making
We are aware that we have the
ability to override any type of
decision that AI tools have
made.
Exploring together
We have an open mindset
around the topic and are willing
to try to implement it in our
processes to better understand
where in the process it make
sense.
AI with colleagues

24. AI Guidelines
Mastery of Prompting
We make sure to stay
knowledgeable and learn the art
of prompting to receive relevant
and accurate responses
Content Quality & Safety
We think twice when we create
prompts to reduce the risk of
getting harmful, biased, or
undesirable content generated.
Prompt Engineering

25. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

26. INSIGHTS & CASES
How we work with AI

27. Two types of AI in our work
Tools
As a help to improve and optimize our own
processes
Products
When AI is part of the products and
services we create

28. Proof by Design
DESIGN PRACTICE
Insight
What is the problem?
Concept development and test
Prototype, test, learn
Development
Iterative process

29. Proof by Design
DESIGN PRACTICE
Insight
What is the problem?
Concept development and test
Prototype, test, learn
Development
Iterative process
Create interview
guide
Plan
workshop/sprint
Competitor analysis
Desk research
Ideation
Transcribe
interviews
Analyze research

30. Proof by Design
DESIGN PRACTICE
Insight
What is the problem?
Concept development and test
Prototype, test, learn
Development
Iterative process
Create concepts
for test
Analyze
user tests
Create test
manuscript
Create text/images to
prototypes
Transcribe
user tests

31. Proof by Design
DESIGN PRACTICE
Insight
What is the problem?
Concept development and test
Prototype, test, learn
Development
Iterative process
Optimize
code
Find bugs
in code
First draft
of code

32. Notion Board
- with examples and how to
get started

33. How frequently do you partner with AI-tools in your work?
Weekly:
I engage with AI tools about once or
twice a week
9
Daily:
AI is an integral part of my workflow 8
Occasionally:
I've experimented but don't use AI
consistently
7
Monthly:
Once or twice a month, I'll use an AI tool 3
Never:
Haven't dabbled in AI tools yet 3

34. Case:
Create
concepts for
user test

35. Creating the concepts

36. Develop the
universe &
characters
/imagine
A woodland scene, from a kids
computer game, a tree surround
by small fairy creatures, pixel art
style

37. The human hand

38. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

39. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

40. Case:
Design sprint

41. Planning the sprint

42. Creating a quick
prototype

43. Transcription

44. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

45. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

46. Case:
Competitor analysis

47. Who & online
presence

48. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

49. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

50. When working with AI in products & services

51. Our approach

52. Case:
Insurance bot
User problem:
It is difficult for the users to sort in
the information on the website to
figure out if they are covered or not

55. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

56. Risks & Challenges
Loss of uniqueness
Generic input will most likely render generic
output, why we need to understand how to
prompt.
Ethics & Biases
Models are a product of the data they were
trained on, in many cases biased.
Hallucination
Models do not have a good or true sense of
reality and may create incorrect information.
Dependent on third-party providers
Becoming dependent on third-party providers
makes us vulnerable to sudden price changes
etc.
Copyright
AI-generated work are constructed from
existing material. Can we use it without
breaking copyright law?
Privacy & Security
How is information we input used? How do we
safeguard confidential data?

57. What now?

58. Two future perspectives
Today
2025
2030
2035
2040
2045
2050

59. Two future perspectives
Today
2025
2030
2035
2040
2045
2050

60. Two future perspectives
Today
2025
2030
2035
2040
2045
2050

61. 76% ljkjlk
30%
15%

62. 76% Have used AI in their work
30% Work in a company with either policies or guidelines
15% Received AI-training from their company

63. AI-course
11-12 October
Sign up via
amanda.stadler@1508.dk

64. Top 3 inspiration
1.Best podcast
AI revolutionen - (in Danish) host: Mikkel Rosenvold & Anders Bæk-
Møller
2.Best talk
Design in Tech 2023: Design and Artificial Intelligence - John
Meada
3.Best AI design ressource
AI meets design toolkit - Tools to help at each step of the design
thinking process to design with and for AI

65. What do you think about
bringing AI into the design
process?

66. Thank you!