Thứ Tư, 25 tháng 4, 2018

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This is AI UX, a miniseries focused

on 10 guidelines created to assist you

in the design and development of AI-based systems.

I'm Daria Loi, an Intel researcher.

And today I will talk about guideline number two,

adopting the minimize intrusion mantra

with a less is more data approach.

The more data you fit into a system,

the more the system will learn, improving its algorithm's

efficiency and accuracy.

Having said that, you must be thoughtful in your data

approach.

When designing and developing AI systems,

use minimalism as a compass.

This means to only collect the data that is necessary for you

to successfully achieve the requested transaction.

For instance, if I recorded you 24/7,

the likelihood for me to accurately understand your life

and use algorithms to predict your future behaviors

would be higher than if I only had

data from a handful of motion sensors in your home.

Yet 24/7 monitoring would be intrusive and exhausting.

You would probably be hesitant to let someone collect data

on you all the time, as your personal privacy

would be compromised.

Just because a massive data collection

could make your AI-based system more advanced,

it does not mean that it should be pursued fully.

There has to be a level of respect and anonymity

for your users to ensure that people will embrace and use

an intelligent system.

Research interviews I conducted made

it clear that the more someone becomes

familiar with an intelligent system, the more they trust

and feel comfortable in using it.

To establish familiarity, careful design

and considerations are needed.

One of the participants in my research

was originally skeptical of smart home systems,

explained that she considered the technology

only after her husband purchased the system.

Once the system reached their home,

she took some time to get familiar with it.

As she grew more familiar and her comfort with the system

increased, she started exploring advanced capabilities

and felt open to embrace more systems

to refine her smart home abilities,

even if that meant allowing her systems to collect more data.

She was able to do this after realizing

the value of the technology through daily use, validating

that it was a safe technology, and after realizing

that the system value-add justified additional data

collection.

Familiarity and trust are crucial if you want someone

to feel confident using your AI system.

This process takes time, patience, and respect

for user preferences.

Based on these findings, I have concluded this recommendation.

Adopt the minimize intrusion mantra and a less

is more data approach.

The minimize intrusion mantra is something

you should always be saying to yourself while designing

for user experience.

You can follow this mantra by setting

the system default settings and a basic level

with basic function.

Additionally, the less is more data

approach should be followed by collecting, using,

and storing only the necessary amount of data.

Make it so the user can change these things

later on once familiarity is established.

A smart system should dynamically

change settings based on direct user's request or feedback

loops.

Keeping your design less intrusive

and being thoughtful about your data collection and usage

will greatly improve your user experience design

and will help the user be comfortable enough

to try your experiences again.

Thanks for watching.

Don't forget to like this video and subscribe.

And I will see you next week on Tuesday for more AI UX.

For more infomation >> AI UX | Minimize Intrusion | Intel Software - Duration: 4:00.

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Antoine, Software architect - Duration: 2:21.

I work on the software for a FADEC, a type of computer mounted as close as possible

to an aircraft's engine.

The FADEC's main job is to control and optimise fuel injection

into the engine.

The team I work with is developing a function to analyse engine

vibrations in real-time.

Would you like to know the three reasons why I love this job?

Then, follow me!

I'm always where the action is and I never have time to get bored.

I have frequent client deliveries

and each one is like a new challenge in which the entire team gets involved

and focuses on the same objective.

We have several types of deliverables: updates following patches,

client-requested modifications, tools, and documentation.

I specialise in Open Source software, which is existing software

that I adapt to the needs of aviation equipment.

Another reason why I love my job: collective wins.

I am lucky enough to work with many people in various trades: my software team members,

the electronics engineers, and colleagues from quality assurance

and industrial production.

As we manage complex software in complex development environments,

we are faced with frequent technical issues.

For example, a client recently requested a major modification

so the FADEC software could be updated from the plane's cockpit.

The entire software chain worked from the first attempt,

to the great satisfaction of everyone involved in its development.

The challenges in the field of onboard aviation software

will continue to grow, and the quantity and complexity of software in aircraft

will increase in the coming years

meaning that engineers will need ever more technical expertise.

I think this is what will keep my job so exciting.

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