A prominent group of researchers
alarmed by the harmful social effects of artificial intelligence
called Thursday for a ban on automated analysis of facial expressions in hiring
and other major decisions. The AI Now Institute at New
York University said action against such software-driven "effect
recognition" was its top priority because science doesn't justify the technology's use and
there is still time to stop widespread adoption.
The group of professors and other researchers cited as a
problematic example the company HireVue, which sells systems for remote video
interviews for employers such as Hilton and Unilever. It offers AI to analyze facial
movements, tone of voice
and speech patterns, and doesn't disclose scores to the job candidates.
Machine learning is a
part of AI which
provides intelligence to machines with the ability to automatically learn with
experiences without being explicitly programmed.
- It
is primarily concerned with the design and development of algorithms that
allow the system to learn from historical data.
- Machine Learning is
based on the idea that machines can learn from past data, identify
patterns, and make decisions using algorithms.
- Machine learning
algorithms are designed in such a way that they can learn and improve
their performance automatically.
- Machine learning
helps in discovering patterns in data.
Natural
Language processing
NLP plays an
important role in AI
as without NLP, AI
agent cannot work on human instructions, but with the help of NLP, we can instruct an
AI system on our language. Today we are all around AI, and as well as NLP, we can easily ask
Siri, Google or Cortana to help us in our language.
The Input and
output of NLP
applications can be in two forms:
Deep Learning
Deep learning is a
subset of machine
learning which provides the ability to machine to perform human-like tasks
without human involvement. It provides the ability to an AI agent to mimic the
human brain. Deep
learning can use both supervised and unsupervised learning to train an AI
agent.
- Deep
learning is implemented through neural networks architecture hence also
called a deep neural network.
- Deep
learning is the primary technology behind self-driving cars, speech
recognition, image recognition, automatic machine translation, etc.
- The
main challenge for deep
learning is that it requires lots of data with lots of computational
power.