Page 23 - AeM_February_2020

BEST
PRACTICES
• Biased Decisions: Systems using machine &
learning process can show biasing many a times. STRATEGIES
Attention should be put to observe why the
machine is biased and how it can be eradicated.

• Decision making and liability: Sometimes
mistakes are made by the AI models, which leads
to serious harm or risk. In such cases, the risk and
responsibility will be borne by whom must be
decided.

• Transparency: To know the accountability of any
action, the clarity of machine reasoning plays the
utmost role. For a series of actions, finding out the
exact root cause is a tedious task.
According to PR Krishnan, “MFDM makes the
enterprise ‘AI-ready’, combining the here and now
• Human values: Human values are very crucial
and sensitive. The AI dealing in place of a human value of automation with the futureproof architecture
must be taught these values so that the machines that allows to incrementally leverage AI capabilities
will act morally and with empathy. from multiple sources.” “Ensuring AI ethical models
will help MFDM in harnessing the process for being
• Data protection: AI can help protect data through more human centric, transparent &explainable, fair,
its intelligent security systems and models. But it safe and trustworthy”, he says. Hence, providing
also paves way for hackers to find new loopholes utmost solutions to the enterprises by balancing all
to hack these systems, which might lead to ethical challenges, implementing guidelines and
several issues like loss of data privacy, robbery of providing solutions has become an integral functioning
crypto currency etc. of MFDM. ◊

• Misinformation: AI can easily be manipulated as By Daniela La Marca
machines do not have the capability of
distinguishing reality from fake. They tend to
believe any information is true if it has evidence.

23 February 2020: Automation & AI: accelerator in digital marketing