This presentation Clearly States that AI bias is not completely harmful for us. This Presentation was made by me for a inter-school competition and I won the 1st Prize. This presentation includes, 1) 'WHAT AI BIAS IS?' 2) 'TYPES OF AI BIAS' 3) 'WHY AI BIAS CAN BE GOOD?' 4)'CASE STUDY OF AMAZON SUCCESS STORY' 5) 'REVIEWS OF FAMOUS PERSONALITIES ON AI' I suggest you to use this presentation and rock in your competition,test, etc

1. Prepared By
Anwaar Alam
AI ETHICS AND BIASES
(For the AI BIAS)
"Intelligence without Ethics
is not Intelligence at all"

2. Presentation
Structure
What is AI Bias?
Types of AI Bias.
Why AI Bias could be good thing?
Case Study of AI Bias.
Reviews.

3. What is AI Bias
Machine Learning bias, also
known as algorithm bias or
Artificial Intelligence bias
refers to the tendency of
algorithms to reflect human
biases.
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4. Types of AI Bias
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Social or systemic biases that discriminate against the specific group(s).
Data sampling that over- or underrepresents specific groups.
The cognitive biases of a data scientist, analyst, or researcher.
In the field of data science, bias is perpetuated by the wrong methods of data analysis,
data collection, clearing and formatting.
Implicit biases representing attitudes and stereotypes we hold about others, even when
we are unaware of it.
The most common AI data bias types are the following:

5. Their real advantage is that they don't get bored or distracted.
Humans need biases because they do not have enough computational
power to take all the available information of their environment into
account.
It is meaningless to build any decision-making system without bias.
However, the purpose of machine learning and A.I. systems is to encode
biases.
Why AI Bias could be a good thing?
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6. AI is biased if (it) weights some factor as material in its prediction when
that factor is not genuinely predictive, but is an artifact of its training
dataset being distorted. This might be because a partial training
dataset was selected in an unrepresentative way, or because there is a
more general societal bias.
AI bias is the basis for any bad outcome in an AI-related sociotechnical
system. It can derive from a weak understanding of a sociotechnical
problem, good data from bad historical events, bad data from any
historical events, biased training, or nefarious designs.
Why AI Bias could be a good thing?
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7. Case Study Amazon Success Story
The role of AI in Amazon's recommendation engine is enormous,
as it generates 35 percent of the company' company's revenue.
Through collecting data from individual customer preferences
and purchases, the company's recommendation engine tends to
personalize the list of products that customers need to
purchase. The massive quantity of data formed or gathered is
used to organize a "360-degree view" of an individual client.
Using that profile, Amazon can find other people who fit into the
same criteria based on hundreds of touchpoints (data sources)
make recommendations for them as well.
Results? The firm reports $87.4 billion in Q4 2019 revenue and
shared that AWS is up 34%, subscriptions (Amazon Prime + Whole
Foods, Videos, and Music) up 32% and Echo, Fire TV, Alexa Voice
Remote (called other), up 41%. Online stores are up 15%. Prime
members pool is now 150 million subscribers, comparing to 100
million two years ago.
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8. Reviews
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"The biggest challenges of AI often start when writing it makes us have to be very explicit
about our goals, in a way that almost nothing else does.”
~Former Googler Yonatan Zunger
“You cannot endow even the best machine with initiative.”
~Walter Lippmanr
“Automation does not need to be our enemy. I think machines can make life easier for
men, if men do not let the machines dominate them.”
~John F. Kennedy

9. Thank You
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