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When things talk, are we ready
to listen?
Thoughts on ignorance and bliss in the internet of things.
About me
Clients
This talk is about the stories we tell
and tell ourselves about data
connected to the physical world.
At play: better, fitter, more productive.
The data ‘opportunity’
Let’s track your activity to help you
become healthier.
Hidden truth
Accelerometer data for health purposes
is extremely inaccurate no matter how
you define ‘health’.
Hidden truth
Gamified health systems enables
obsessive behaviour and eating
disorders.
Hidden truth
Most people discard their wearable
within a 6 month period.
See PWC report from 2014.
Data hypocrisy
That data gathering about your own
body isn’t another form of fashion and
cultural mimicry.
We are offering very little more than a
pedometer would but at 100 times the
cost.
Data hypocrisy
Because if you can’t answer the
question ‘how are you doing’ without
checking a device, there’s something
else going on.
At work: better, fitter, more productive.
The data ‘opportunity’
Let’s track your gym attendance, the
number of steps you take so we can
make sure everyone works to the
best of their potential.
Hidden truth
What you can guess from activity does
not translate into a perfect picture of an
employee’s ability to do great work.
Nor should it unless your job absolutely
depends on it.
Hidden truth
What if someone has cancer, AIDS
or another medium / long term
chronic illness.
An employee isn’t a liability by
default, it should always be an asset
first.
Data hypocrisy
Older people do great work, they
have helped you build your
company.
They are probably the ones coming
up with these policies.
In the home: compulsive shopping disorder.
The data ‘opportunity’
Let’s track what you buy and help
you buy it more quickly next time.
Hidden truth
We spend too much, especially
using credit.
Even IKEA’s head of sustainability
says we have reached ‘peak stuff’.
Apple sales are shrinking for the first
time in 15 years.
Data hypocrisy
Banking apps that help me budget
rarely connect to any of the e-
commerce services we use
compulsively.
In the home: the grandma problem.
The data ‘opportunity’
Let’s track the elderly so we can
bring them care at the right time.
In-home care is very expensive.
Care homes even more.
Hidden truth
Older people want to stay at home
as long as they can but…
Nearly half of older people (49% of
65+ in the UK) say that television or
pets are their main form of company
See York Health & Wellbeing Study 2014
Data hypocrisy
Are we giving families an excuse to
‘monitor’ instead of doing the hard job
of caring, engaging and supporting an
ailing family member.
In the city: transportation hell.
The data ‘opportunity’
Let’s track cars, buses, cyclists to tell
us when there is traffic and where it
is.
See Nominet Smart Cities Report September 2016.
Hidden truth
Chances are your city has too many
cars and not enough clean, reliable
public transportation options.
That’s it.
Innovation hypocrisy
Car lobbies are powerful and want to
keep you relying on an industrial sector
(steel, aluminium, semiconductors, etc)
that matters to sizing GDP no matter
what the fuel is or who is driving.
See the steel buyouts in the UK.
What now?
Maybe the answer is small, obtuse
data that only makes sense
to a small group of people,
or is unrelated to them altogether.
In the home: Good Night Lamp.
Data opportunity
A lamp on, only means what you want it
to mean because you’ve established a
‘language’ with your family.
In the city: Giving things a voice.
Data opportunity
A bridge is interesting for it’s
immediate neighbourhood.
A lamp is interesting to pedestrians on
that street.
I’m not saying
the internet of things is
about industrial
applications only.
I am saying people need to be
involved in owning a data
experience and making it theirs.
Data Brick
(work in progress
and an invitation)
thegoodhome.org
Data Brick
What if your home held locally, in a brick:
•  Land Registry
•  Room sizes
•  Plans
•  How wires were connected
•  Aggregated anonymous energy consumption
•  How to use appliances
•  General maintenance log (what plumbers you used)
•  Building insurance
•  Tax agreements
Data Brick
And you create and eventually leave with:
•  Who lives in the house
•  Who visited you (care providers, etc)
•  Other bills
•  Data collected for billing purposes
•  Stuff you own
•  Insurance
•  Mortgage information
•  Contracts
Because data can also be
collective in a lateral way.
You may never meet your
community.
Question what is hiding behind your data.
Find out what behaviours are you really
enabling, good and bad.
Think about what is the alternative to using
your product.
In conclusion
Think about your data as unrelated to a
person.
Think about your data as small, local,
perhaps stuck somewhere.
Think about the people who have to
interact with it and their needs.
In conclusion
Data is a slave to use.
Use is a slave to experience.
Experience is a slave to culture.
Because
And remember kids:
Vielen dank
designswarm.com
goodnightlamp.com
thegoodhome.org
iot.london
alex@designswarm.com
@iotwatch

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When things talk, are we ready to listen?

  • 1. When things talk, are we ready to listen? Thoughts on ignorance and bliss in the internet of things.
  • 4. This talk is about the stories we tell and tell ourselves about data connected to the physical world.
  • 5. At play: better, fitter, more productive.
  • 6. The data ‘opportunity’ Let’s track your activity to help you become healthier.
  • 7. Hidden truth Accelerometer data for health purposes is extremely inaccurate no matter how you define ‘health’.
  • 8. Hidden truth Gamified health systems enables obsessive behaviour and eating disorders.
  • 9. Hidden truth Most people discard their wearable within a 6 month period. See PWC report from 2014.
  • 10. Data hypocrisy That data gathering about your own body isn’t another form of fashion and cultural mimicry. We are offering very little more than a pedometer would but at 100 times the cost.
  • 11. Data hypocrisy Because if you can’t answer the question ‘how are you doing’ without checking a device, there’s something else going on.
  • 12. At work: better, fitter, more productive.
  • 13. The data ‘opportunity’ Let’s track your gym attendance, the number of steps you take so we can make sure everyone works to the best of their potential.
  • 14. Hidden truth What you can guess from activity does not translate into a perfect picture of an employee’s ability to do great work. Nor should it unless your job absolutely depends on it.
  • 15. Hidden truth What if someone has cancer, AIDS or another medium / long term chronic illness. An employee isn’t a liability by default, it should always be an asset first.
  • 16. Data hypocrisy Older people do great work, they have helped you build your company. They are probably the ones coming up with these policies.
  • 17. In the home: compulsive shopping disorder.
  • 18. The data ‘opportunity’ Let’s track what you buy and help you buy it more quickly next time.
  • 19. Hidden truth We spend too much, especially using credit. Even IKEA’s head of sustainability says we have reached ‘peak stuff’. Apple sales are shrinking for the first time in 15 years.
  • 20. Data hypocrisy Banking apps that help me budget rarely connect to any of the e- commerce services we use compulsively.
  • 21. In the home: the grandma problem.
  • 22. The data ‘opportunity’ Let’s track the elderly so we can bring them care at the right time. In-home care is very expensive. Care homes even more.
  • 23. Hidden truth Older people want to stay at home as long as they can but… Nearly half of older people (49% of 65+ in the UK) say that television or pets are their main form of company See York Health & Wellbeing Study 2014
  • 24. Data hypocrisy Are we giving families an excuse to ‘monitor’ instead of doing the hard job of caring, engaging and supporting an ailing family member.
  • 25. In the city: transportation hell.
  • 26. The data ‘opportunity’ Let’s track cars, buses, cyclists to tell us when there is traffic and where it is. See Nominet Smart Cities Report September 2016.
  • 27. Hidden truth Chances are your city has too many cars and not enough clean, reliable public transportation options. That’s it.
  • 28. Innovation hypocrisy Car lobbies are powerful and want to keep you relying on an industrial sector (steel, aluminium, semiconductors, etc) that matters to sizing GDP no matter what the fuel is or who is driving. See the steel buyouts in the UK.
  • 30. Maybe the answer is small, obtuse data that only makes sense to a small group of people, or is unrelated to them altogether.
  • 31. In the home: Good Night Lamp.
  • 32. Data opportunity A lamp on, only means what you want it to mean because you’ve established a ‘language’ with your family.
  • 33. In the city: Giving things a voice.
  • 34. Data opportunity A bridge is interesting for it’s immediate neighbourhood. A lamp is interesting to pedestrians on that street.
  • 35. I’m not saying the internet of things is about industrial applications only.
  • 36. I am saying people need to be involved in owning a data experience and making it theirs.
  • 37. Data Brick (work in progress and an invitation) thegoodhome.org
  • 38. Data Brick What if your home held locally, in a brick: •  Land Registry •  Room sizes •  Plans •  How wires were connected •  Aggregated anonymous energy consumption •  How to use appliances •  General maintenance log (what plumbers you used) •  Building insurance •  Tax agreements
  • 39. Data Brick And you create and eventually leave with: •  Who lives in the house •  Who visited you (care providers, etc) •  Other bills •  Data collected for billing purposes •  Stuff you own •  Insurance •  Mortgage information •  Contracts
  • 40. Because data can also be collective in a lateral way. You may never meet your community.
  • 41. Question what is hiding behind your data. Find out what behaviours are you really enabling, good and bad. Think about what is the alternative to using your product. In conclusion
  • 42. Think about your data as unrelated to a person. Think about your data as small, local, perhaps stuck somewhere. Think about the people who have to interact with it and their needs. In conclusion
  • 43. Data is a slave to use. Use is a slave to experience. Experience is a slave to culture. Because