creativity techniques for computer scientists

1 Challenge the future

Creativity Techniques for computer scientists

Marco Cattani Embedded Software Group, Delft University of Technology


Classic Brainstorming

•  Find small group of persons • Define initial topic/problem • Make sure topic is clear • Avoid criticism and aim at

quantity (facilitator)

• Clarify and combine ideas •  Select valuable ideas

•  Structured •  Schedule who can speak •  Write ideas on post-it

• Un-structured •  Everyone can speak at

anytime

Generate new, valuable ideas by interacting with others


How to improve our creativity?

• Diverge •  Exploration •  Diversification

• Converge •  Focus •  Selection

… it works even with tea!

Before coffee the ideas, after coffee criticism Alex Osborn


DIVERGE Create new ideas


Biomimicry

•  Find parallelism •  Study nature’s solution • Adapt solution Example Ant colony optimization, epidemic protocols

Imitate nature to solve our problems


Personal analogy

•  Personify the subject with human characteristics

• Role playing ( e.g. feelings) • Connect analog and subject

Example Human behaviors in network protocols (gossip, 3-way handshake, routing)

Identify with a process/concept to get a new point of view


Osborn checklist

• Adapt/Modify/Substitute? • Magnify/Eliminate? • Rearrange/Reversal? • Combine/Other use?

Example Image processing techniques for graphs (edge detection)

Develop new solutions from existing ideas


Challenge assumptions

•  List the problem assumptions • Chose 1 and challenge it •  Solve problem from this new

prospective

Example What is computers have no storage or energy supply? (Cloud, Autharkic Computing)

Removing a core assumption to create an innovative idea/product


Random input

•  Select a random noun (concrete or known)

• Use this work as a starting-point for the brainstorm

Example Solution initialization in problem optimization

Link another thinking pattern into the one we are using using random stimuli


Redefinition

•  State original, narrower, broader problem

• Why we want to solve it? • What stops us from that?

Example Overcome wireless channel congestion with VLC

Hierarchically redefine our problem to find more general/specific solutions


Medici effect

•  Select an unrelated field •  Search for solution to analog

problem in that field • Adapt the solutions

Example Leader election, simulated annealing

Exploits how ideas in seemingly unrelated topics/fields intersect


Misunderstanding

• Define some constrains • Describe an existing solution • By misunderstanding, we

create a new solution

Example Mouse with no buttons, from an un-finished apple prototype

Create new solutions when trying to understand an existing one


Reverse Brainstorming

•  Identify different ways of causing the problem

•  Find ways of prevent this causes to happen

Example Ex hackers that invents new security techniques

Causing the problems is the first way of learn how to solve them


SIT (systematic inventive thinking)

• Remove components • Make one of more copies • Divide into parts (modular) • Unify tasks into 1 component

Example Multi-channel mac protocols, object oriented programming

Subtraction, multiplication, division, unification


CONVERGE Select valuable ideas


COCD-Box

Everyone put a colored post-it on each idea based on its originality and feasibility

• Consider green ideas • Discard blue ideas • Keep yellow ideas for later

Detect innovative, feasible ideas using a classification technique


Force-field analysis

Plot opposing forces (proportional) and draw conclusions

•  Overall force? •  Increase for? •  Mitigate against?

For Against

Understand the forces for and against an idea


100 euro test

Assume you have 100 euro • Allocate money to ideas • After everyone finish, review

your decision •  Select richest ideas

Idea $1 $2 Total

On which idea will you spend your money?


Negative selection

Review the problem definition •  Sort into no and maybe • Repeat if necessary

Idea No Maybe

To shorten a long list of ideas by finding what is wrong with each idea


NUF test

Grade each idea from 1 to 10 on three parts

•  New: never tried before •  Useful: solves the

problem •  Feasible: can be

implemented in practice

Check if an idea is likely to be effective and work in practice

Criteria Score Comm.

New

Useful

Feasible

TOTAL


PINC filter

Discuss each idea and add notes to each section

•  Positives: add values •  Intriguing: could be of value • Negatives: remove values • Concerning: could remove

value

Idea

Positives Negatives

Intriguing Concerning

Evaluate deeply a short list of ideas


Conclusions

• Creativity can be improved with some training and few tricks

• When you try to solve a problem, you are not programming. Break the rules and don’t stay inside the lines

•  Innovation is not creativity. Once you generated lots of ideas, it is time to select and elaborate the most promising ones

Few more words about the creativity process:

creativity techniques for computer scientists

Self Improvement