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In this heyday of A.I. innovation, organizations are pouring tens of billions of dollars into A.I. development. However, for all the money invested in capabilities, there has not been commensurate investment in A.I. governance.
Some companies may take the position that when world governments release A.I. regulations, that will be the appropriate time to wrestle A.I. programs into a governance structure that can address complex topics like privacy, transparency, accountability, and fairness. In the meantime, the business can focus solely on A.I. performance.
Regulatory wheels are already in motion. However, regulations move at the speed of bureaucracy, and A.I. innovation is only accelerating A.I. is already deployed at scale, and we are rapidly approaching a point after which A.I. capabilities will outpace effective rulemaking, putting responsibility for self-regulation squarely in the hands of business leaders.
The solution to this puzzle is for organizations to find the balance between following existing rules and self-regulation. Some companies are rising to the responsible A.I. challenge: Microsoft has an Office of Responsible A.I. Use, Walmart a Digital Citizenship team, and Salesforce an Office of Ethical and Humane Use of Technology. However, more organizations need to quickly embrace a new era of A.I. self-regulation.
Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.
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