Ethics of Facial Recognition: How to Make Uses Fair and Transparent

It’s time to figure things out.

Building AI for a reason, not just because one canThe popularity of AI gained momentum after the conference in 1965 when a scientific community first united to study ways to replicate a human brain and enable machines to undertake activities only humans could do.

Since that time, computational power and positive experience in the field of data science has dramatically scaled up.

To date, latest tech stack, AI libraries and frameworks allow programmers to build a broad range of AI-based solutions and applications that fit various business needs.

While using some provided tech stack, they may pay insufficient attention to the core principles of development.

That is to say, ethical principles.

Too many of them can create quality applications, but few ask themselves about the ethical aspects of building something novel.

As one of the world leaders in the field of facial recognition, Microsoft expresses concern about the ethics of AI.

They have figured out 6 core principles to help make the development more meaningful.

6 pillars of ethical usesSharing his view, Brad Smith, Microsoft, said, “Advanced technology no longer stands apart from society…, our personal and professional lives.

This means the potential uses of facial recognition are myriad.

” The technology is capable of influencing not only business development strategies but also communications, day-to-day personal life, routine tasks, the reputation of one or another organization on the market as well as its reputation among employees.

Some cases of using facial recognition technology brought to light algorithmic bias and raised doubts about transparency and legitimacy.

Let’s take for instance the image recognition algorithms in Google Photosthat uncovered racial biases or the face-scanning system in Orlando International Airportthat raised concern over the accuracy of scanning and the fact that there are no strict regulations on how to work with passengers who were misidentified.

Given all this, it seems wise to keep an eye on observing guidelines while creating and using facial recognition systems.

And here are 6 fundamental ones:FairnessReliability and safetyPrivacy and securityInclusivenessTransparencyAccountabilityEthical guidelines for gathering and disposal sensitive data have already seized the attention of adopters of facial recognition.

To reinforce the results, it’s crucial that each particular organization perceives regulations as a question of paramount importance.

Playing a fair and transparent gameInnovations seem creepy unless they are well explained to the public at large.

On weighing all pros and cons and deploying face recognition software, an organization will most certainly face the issues of justified gathering and using personal data for facial recognition.

Sticking to the following principles can help make things go right:Inform about the use of the technology in any public area.

It can help avoid possible awkward discussions about the legitimacy of keeping visitors uninformed and violation of privacy.

Be watchful on datasets.

A facial recognition system is as smart as a training dataset is inclusive.

For instance, comprehensive data can help avoid racial bias.

But perfection always lies out of reach.

Ideally, it’s better to elaborate a strategy on how to treat people whom facial recognition misidentified.

Each organization may apply specific measures to ensure a balanced approach to the problem and create a good image.

Share information about personal data storage.

The work of a facial recognition system can provoke prejudice against further uses of sensitive data.

Another responsibility of each organization is to ensure private and secure storage of data.

An organization should be ready to explain the reasons for processing personal data, inform about any unintended misuses and have clear evidence that the use of data is fully transparent and legitimate.

Train and raise awareness.

Any new technology brings both social benefits and concerns.

But it doesn’t mean having one’s head in the sand.

Oliver Schabenberger, SAS, admits, “Even for many sophisticated users, AI still is a black box.

” More importantly, he suggests that it is time to illuminate this black box, in other words, observe its work and explain the pros and cons of using it.

If everyone within an organization comprehends the principles of using data for face recognition, they will calmly respond to bias.

This kind of faith in new technology is indispensable.

The use of any technologies can equally be for good or evil.

Artificial intelligence is developing by leaps and bounds to assist humans in transforming the present-day reality to the better.

However, meaningless tech development may lead to social misunderstanding and provoke ethical debates.

Thinking ahead and keeping regulations in mind — that’s what can help build a brilliant future of facial recognitionEnjoyed this article?.Find more stories here: https://indatalabs.

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