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Machine LearningBy Alex Scarlatos

What is Machine Learning?Machine Learning is the process by which computers can be trained through

observation, rather than being explicitly programmed.

Basically, a program is given input and adjusts its behavior based on that input.

While ML is an important part of Artificial Intelligence, they are not the same thing.

AI is the ability for a machine to “think” on its own, and many research fields are

encompassed by AI.

Example - A Personalized Music Station1. The station picks a random song - “Baby” by Justin Bieber.

2. The user gives the song a dislike.

3. This is interpreted as -1 points for pop music and male singers.

4. The station then picks a random song, but sways the randomness so there is some less

chance of getting a pop song or a male singer - it picks “Rain Is A Good Thing” by

Luke Bryan.

5. The user gives the song a like.

6. The algorithm gives +1 points to country music and gives a point back to male singers.

The station remembers user choices, and when a trend appears it will be accentuated. If the

user keeps liking country songs and disliking other genres, the station will eventually only

pick country songs.

Where we see ML today

https://techcrunch.com/2016/09/06/ultimate-guide-to-the-news-feed/

Microsoft’s ML Twitter ExperimentIn 2016, Microsoft released a chatbot named Tay onto Twitter. People could tweet at it

and it was supposed to respond in relevant ways, and was meant to evolve through

these interactions.

http://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist

So what is ML actually good for?

Medical DiagnosesComputer algorithms can analyze millions of medical cases and draw conclusions

based on strong data patterns.

When a new patient comes in, the program can compare their condition and medical

history to previous cases and make a diagnosis.

This is expected to give much more accurate predictions when determining a patient’s

remaining time or chance to live.

Protein FoldingGiven previously found

folds, a program can

predict new folds by

considering where others

were successful.

This can save researchers

time and money.

http://www.mdpi.com/1422-0067/17/12/2118/htm

Autonomous CarsThe car is “trained” by drivers.

It records what directions

people turn in certain

situations and will make its

own decisions based on

analysis of those choices.

https://www.coursera.org/learn/machine-learning/lecture/zYS8T/autonomous-driving

So where does this lead us?

How can ML affect our culture?Machine Learning algorithms are capable of actually generating music. While this is

unlikely to entirely replace human writers, a good portion of the music industry could

theoretically become automated.

“People have to get the idea out of their head that music comes from great individuals.

It doesn’t, it comes from communities, it comes from societies. It develops over many

years and computers become a part of societies.” - George Lewis, music professor

https://www.washingtonpost.com/news/innovations/wp/2016/06/06/googles-computers-

are-creating-songs-making-music-may-never-be-the-same/?utm_term=.4d8cdfda622a

Will robots actually take our jobs?By analyzing the ways that humans perform tasks, machines can gradually replace us

at these tasks.

This mostly applies to simple tasks that are repetitive and easily describable.

http://www.bbc.com/news/technology-34066941

This might not all be bad news thoughTechnology has been advancing rapidly since the Industrial Revolution, and people

have always been afraid of being replaced.

Technology improves quality of life for workers and consumers.

We have always adapted to our technology, and while the future is unpredictable we

shouldn’t expect this time to be very different.

https://www.youtube.com/watch?v=UqESogRgrYw

What can we take away from this?1. ML isn’t the answer to all of our problems...

(Do we really want as susceptible as Microsoft’s Twitter bot making national

security decisions?)

2. Many modern jobs will be replaced. But this is inevitable and could actually

improve quality of life if society is adjusted properly.

Resourceshttp://www.dataversity.net/ai-vs-machine-learning-vs-deep-learning/

http://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist

https://www.statnews.com/2016/10/03/machine-learning-medicine-health/

http://www.mdpi.com/1422-0067/17/12/2118/htm

https://www.coursera.org/learn/machine-learning/lecture/zYS8T/autonomous-driving

https://www.washingtonpost.com/news/innovations/wp/2016/06/06/googles-computers-are-creating-songs-maki

ng-music-may-never-be-the-same/?utm_term=.4d8cdfda622a

http://www.bbc.com/news/technology-34066941

https://www.youtube.com/watch?v=UqESogRgrYw