The CSPAI program is designed to bridge the gap between cybersecurity professionals and the rapidly evolving world of AI. It equips individuals with the knowledge and skills necessary to secure AI systems, ensuring their integrity, confidentiality, and availability. This program is a significant step towards building a robust cybersecurity ecosystem in India, fostering innovation and trust in the AI landscape.
While addressing the gathering, the Director General of CERT-In said “This incisive and timely CSPAI program by SISA empowers professionals with comprehensive expertise to gain understanding of AI systems and to be proactive against the new spectrum of threats. As first of its kind ANAB-accredited AI Security Certification program, this course is perfectly attuned to the rapidly evolving threat landscape of AI in cybersecurity. The curated course has the blend of all the key elements of AI security and will enrich the skills to adapt and deploy secure and trustworthy AI in work environments. The program would open up a trove of opportunities and demand for emerging AI related job roles. The joint certification program is another accolade in CERT-In’s efforts to foster Public-Private Partnership.”
Mr. Dharshan Shanthamurthy, Founder and CEO of SISA, shared his vision for the CSPAI program, “The launch of the CSPAI program perfectly complements our Cyber Nalanda initiative, which commenced with last week’s foundation stone laying ceremony, to tackle future cybersecurity challenges. This program reflects our unwavering commitment to solving the most pressing security issues in India, and globally. By equipping professionals with the tools and knowledge to safeguard AI systems, we are building a safer digital future, driven by innovation and responsibility. We also believe that certified professionals from this program will enhance organizational security postures, reduce the likelihood of breaches, and build greater trust with customers and stakeholders”.
Renju Verghese highlighted the importance of ethical considerations in AI development. She emphasized that AI systems should be developed with a focus on fairness, transparency, and accountability. She illustrated this point with the example of facial recognition technology, where biased algorithms can lead to discriminatory outcomes.
