TY  - JOUR
T1  - Artificial Intelligence: Risks and Opportunities
AU - De Oliveira, Alisson Paulo AU - Tadeu Braga, Hugo Ferreira 
JO  - International Business Management
VL  - 14
IS  - 7
SP  - 236
EP  - 243
PY  - 2020
DA  - 2001/08/19
SN  - 1993-5250
DO  - ibm.2020.236.243
UR  - https://makhillpublications.co/view-article.php?doi=ibm.2020.236.243
KW  - Artificial neural nets
KW  -hot-rolled structural sections
KW  -prediction
KW  -autonomous direction
KW  -theory
AB  - This study aims to discuss the risks and
opportunities involved in building predictive models
based on artificial intelligence. Countermeasures are also
proposed to minimize the risks involved in their adoption
where reliability is a critical factor for user safety such as
autonomous driving. For this, it is explored a real
development of a predictive mathematical model, using
industrial data in the steel industry. This development
aimed to construct an empirical mathematical model to
predict the mechanical properties (Yield Strength, YS) of
hot rolled steel structural beams. Such model was based
on rolling process variables and the chemical composition
of steel. As a result of this research it was observed that
the obtained data agreed with the expected metallurgical
theory. The errors obtained between the estimated and the
real values were greater for process conditions with lack
of enough data. These results are associated with the risk
of using artificial intelligence technology in critical
applications and actions aiming at its improvement are
proposed.
ER  -