Seven principles for a Responsible AI
1-Social responsibility
The responsibility for AI use requires effective regulations accepted
and supported by society. It is necessary to be conscious of the benefits and
dangers of its use, promoting citizen participation in public politics
formulation. An indiscriminate use of AI could standardize human creativity.
2-Assure diversity
Considering ethnic, cultural, and generational perspectives from a
multiple and trans disciplinary approximation in all development periods to achieve
emphatic interaction of society with AI systems.
3- Preserve vulnerable groups
Children, active technology users, must receive special attention in the
AI system´s design to guarantee no harmful interactions that impact their
cognitive and emotional development by the link replacement. It must consider
people with different abilities and advanced ages challenges, among other
groups.
4-Bias control design
Like any intelligence, AI also has bias effects. Its decisions turn out
biased by the cultural information it has been trained on. This situation can
result in operational and discriminating risks. Multidisciplinary experts must
work together to identify and mitigate these risks, from design to
implementation.
5-Civil rights guarantee
AI could have a significant impact on civil rights by preventing personal
identification, manipulation, or unequal access to opportunities. The balance
between technological innovation and civil rights preservation is fundamental
in a requirement to achieve socially responsible AI.
6-Mental health control impact
Artificial Intelligence (AI) is employed for the identification and
mitigation of mental health issues. Conversely, excessive exposure, link
substitution, and the consideration of AI as universally comprehensive
knowledge may impact human creative potential.
7-Guarantee human autonomy in decision-making
AI systems should be designed to augment human capabilities rather than
replace them. This necessitates discretionary decision-making with implications
for various domains, including family, education, and legal matters, among
others. Humans, who are inherently beyond reducible statistical and algorithmic
predictions, must play a crucial role in distinguishing the nuances of each
decision area for AI.
Leave a Reply