AI News, Artificial Intelligence: Taking the Good With the Bad
- On Sunday, June 3, 2018
- By Read More
Artificial Intelligence: Taking the Good With the Bad
Over a year ago, I started researching artificial intelligence (AI).
As a marketer for a company with an advanced digital solution that uses AI-type technology, I thought it was important for me to know the competition and learn about solutions that could help me currently and in the future.
Throughout my research, I found both pros and cons to AI, and it inspired me towrite an article in which I argued the benefits of AI outweigh the risks.
lot has transpired since I wrote the piece in February 2017, but my argument that tech adoption is slow and therefore it will be years before AI reaches its full potential is still valid.
Even though we are seeing incremental progress in the role AI plays in our day-to-day lives, the change has been so gradual that, without a bit of research, it’s hard to tell the difference between today and a year ago.
I’m going to look at AI from two points of view: How the technology affects us in our day-to-day lives, and how it is making inroads toward real change in professions such as medical science.
Because companies have to try harder and harder to rise above the noise, they are more and more willing to invest in marketing technology —
I spend half my day deleting spam with pitches for the latest and greatest personalization methods from vendors that should try some sort of personalization before marketing to me —
There are some extraordinarily intelligent people at work making excellent technology, but often that technology is expensive, which is why AI is tailored for companies that can afford it or companies in the business of gathering data.
While those scenarios seems like the scary futuristic stuff of science fiction, in my opinion it is far less scary than the way AI is used in data collection and analysis.
Both doctors and patients benefit from advanced technologies that help medical professionals do a better job of keeping people healthy.
When machine learning is applied in medicine, a machine can become a superdoctor, spouting out case histories and suggesting possible treatments that could take an entire medical team weeks to think of.
- On Monday, February 17, 2020
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