By Chetan Anand
Artificial intelligence (AI) and machine learning (ML) are shaping the future. They have the potential to create new ways of working and bring tremendous opportunities – but only if their use is effectively managed.
AI/ML is impacting almost every industry in the world, from biotechnology to information technology, from medicine to music, from education to manufacturing, from transportation to retail, and so on.
For instance, artificial intelligence in biotechnology can speed up drug discovery, deliver analytics, accurately diagnose medical conditions, edit gene structures, develop personalized medicine, and do much more to help mankind. When it comes to cybersecurity, AI can monitor, analyze, detect, and respond to cyber threats in real time. In the field of medicine, AI algorithms can analyze medical images, such as X-rays and MRIs, with greater accuracy and speed than human radiologists, often detecting diseases such as cancer at earlier stages. From a music point of view, AI can help correct vocal pitch and allow engineers to mix and master recordings much more quickly and cheaply. The Beatles recently used AI to isolate John Lennon’s voice from a late 1970s demo, stripping out the other instruments and ambient noises in order to build a new, pristinely-produced song, ‘Now and Then.’
An example of how AI is used in the field of education is tutoring: AI systems can gauge a student’s learning style and pre-existing knowledge to deliver customized support and instruction. Another example is that AI can help grade exams using an answer key; but it can also compile data about how students performed and even grade more abstract assessments such as essays. AI systems that use machine learning algorithms can detect buying patterns in human behavior and give insight to manufacturers.
AI for transportation can help reduce the risk of road accidents and enhance safety by informing drivers with real-time updates about traffic conditions and potential hazards. AI helps improve fuel efficiency by assisting drivers in making informed decisions about when and how to accelerate and brake. Metropolitan cities in India are set to deploy AI-enabled cameras on highways connecting the city. AI in retail use cases include frictionless self-checkout, smart shelves, and automated inventory management. The future looks optimistic with more and more applications of AI/ML.
The flipside of any emerging technology is that it brings technology risks. According to ISACA’s latest survey on AI, the top five risks of AI include misinformation / disinformation, privacy violations, social engineering, loss of intellectual property (IP) and job displacement. The advent of this technology has also paved the way for increased trends in cybercrimes.
The survey also indicates that use of generative AI is ramping up, but organizations are not yet prepared with policies, training and effective risk management. Forty-two percent of organizations say their companies permit the use of generative AI, yet 70% believe employees are using any type of AI and 60% believe employees are using generative AI. However, 40% of organizations offer no AI training at all, and 32% say training is limited to staff who work in tech-related positions.
This emerging technology has also instilled a sense of fear among professionals when it comes to job security. While AI/ML may be viewed as a cost-cutting technology, at the same time, it creates potential opportunities. What this translates to is that professionals need to equip themselves by acquiring AI/ML skills to embrace the changing technology landscape and stay relevant to their organizations. The fact that organizations cannot entirely rely on AI/ML is true, and it does require human intervention even after adopting the technology. As an example, generative AI can be used to create organizational policies. However, the information generated by AI cannot be directly consumed. It needs to be validated for accuracy and tailored to suit organizational needs.
The new technology has also given rise to new legal and regulatory requirements and standards. For example, the European Union (EU) has already enacted the AI Act, and many countries are coming up with legislation on AI. The National Institute of Standards and Technology (NIST) in the US has released their AI Risk Management Framework, and the International Organization for Standardization (ISO) has recently published the ISO/IEC 42001:2023 – Information technology Artificial Intelligence Management System (AIMS).
Competence is required to ensure compliance with legal and regulatory requirements, to assess AI/ML-related risks and to implement AIMS. The good news is that competence cannot be entirely replaced by AI. It is worthwhile to get trained in AI/ML standards/frameworks and add value to the organization and its entire supply chain to produce smart solutions and services.
In conclusion, the impact of AI on society is both exciting and challenging. AI has the potential to transform the way we work, communicate, and interact with technology, but it also raises concerns about the displacement of jobs, bias and discrimination, and the potential for misuse or abuse. Therefore, AI/ML technology needs careful consideration and risk assessment before its adoption.
Author: Chetan Anand, CDPSE, National Cyber Security Scholar, CCIO, ICBIS, ICCP, ICOSA, CPISI, OneTrust Fellow of Privacy Technology, IRAM2, ISO 27001 LA, ISO 22301 LA, ISO 27701, ISO 31000, ISO 9001 LA, Lean Six Sigma Green Belt, NLSIU Privacy and Data Protection Laws, SQAM and Agile Scrum Master
Associate Vice President – Information Security and CISO, Profinch Solutions, ISACA Global Mentor and Volunteer.
Disclaimer: The views expressed by the author are solely the author’s and do not reflect the views and beliefs of Profinch Solutions and ISACA; their affiliates, or employees.
