The Impact of Artificial Intelligence on Organization’s Security

The new-age technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Robotics are driving the biggest technological and organizational changes since the 4th Industrial Revolution. However, these are associated with potential opportunities as well as risks. An absence of a robust security framework can lead to uncontrollable damages.

In ancient times, the land was the most important asset in the economy. In the last 200 years machines replaced land as the most important economic asset. And as of today, data and Artificial Intelligence (AI) are replacing machines as the most important asset. Everybody wants to own and control the flow of data in the world.

Artificial Intelligence is Omnipresent – Why do organizations place so much faith in AI?

Over the past few years, Artificial Intelligence is shaping our lives in more ways than we can imagine. From how education has transformed to how economies operate, there exists no area where AI has not had an outsized impact. The Global Artificial Intelligence (AI) market size is likely to grow at a CAGR of almost 21% with US$ 76.44 bn between 2021-2025. 

Artificial Intelligence

The presence of AI is felt in almost every industry including defence. AI or specific forms of it, such as machine learning (ML), have a wide array of applications. A classic example during these unprecedented times is the use of AI chatbots and robots in hospitals that check for temperature and Covid-19 symptoms. 

They are increasingly popular in sectors that deal with enormous amounts of data. Most organizations adopt AI for it reduces human interference for analyzing massive amounts of data and correlating the data with various reference points. This makes the job of the decision-maker simpler given the competition. 

On the other hand, there are certain organizations that adopt AI just for the thrill of it without understanding the security consequences. The question to ask here – Is the security and privacy of AI-ML systems any different from what is seen in traditional computer security?

Artificial Intelligence Carries Risks

While there is a lot of excitement around AI and its applications across industries, the security aspect of AI often takes the back burner. There are two prime risk factors that organizations tend to overlook. 

  • Hackers can back door their way into Organization’s Records

Imagine one of your employees clicking on a malware link through a phishing email. This causes severe damage to her computer on the server, which can be contagious. On being notified, other co-workers on the server think twice before clicking on the malicious link. Hence the risk can be assessed and managed thereon. Now consider the same scenario with an AI. 

When you take people out of a business equation and rely on AI, the virus is likely to spread much faster giving hackers full control. They then target the system to which the AI is trying to access, and re-route them to malicious databases for their malicious deed. If attackers have access to the data which the AI acts upon, they can implement malicious campaigns, and compromise the intent and objective of the AI that could lead to deadly and serious damages or financial losses.

  • Data Integrity in AI Algorithms

The recently popular Tesla self-driving car failed its Autopilot feature that runs on AI and deep learning algorithms. While AI has become very good at detecting objects in real-time. But they do have some distinct limits that manifest themselves in the failures we see in self-driving cars. 

Another example is the smart voice assistant application on IOS – Siri or google based Google echo. These apps typically do what you ask them to, like play a song or call this person, etc. However, they assist you as long as they understand your patterns and the context of the question. 

AI models lack the common sense that humans have. They know nothing about the rules of gravity, the relations between different objects, the common behaviors of people, and other things that directly affect the decisions humans make. The AI algorithms need to be explicitly instructed on every single scenario through more data in the form of texts, videos, podcasts, etc. 

Other potential risk factors include loss of privacy due to the amount and type of data to be consumed, over-reliance on a single, master AI algorithm, lack of understanding of the limitations of the AI algorithm, and insufficient protection of data and metadata. 

Minimizing Organizational Risks while Adopting Artificial Intelligence

Ideally, organizations must strike a careful balance between machine learning and human intelligence. For example, security experts can create policies that enable AI to filter out events that don’t pose high-security risks. Conclusively, human intuition, expertise, and experience help fill in the evaluative gaps that machine learning cannot and determine which activities cross the line and which ones do not. Human-supervised AI provides a much more accurate model than an unsupervised alternative in security situations. 

For organizations – large or small, start-ups or long-running some of the best practices involved in minimizing risks while still adopting AI are:

Understand your current use cases and the purpose of building an AI application. For starters, AI is not recommended for making financial decisions or performing surgery unless the algorithm undergoes thorough testing. 

AI is constantly evolving, it’s crucial that organizations have security experts on call. Understand the data and its limitations on AI networks. Determine the data sources best suited for your organization. The decision-making capabilities should not completely rely on AI models as AI still has a long road ahead of it before it can match the skills and savviness of a human analyst.

Performing extensive testing involving various parameters and constant monitoring of the AI model along with tightening security gates is crucial. Using protocols such as authorization and authentication, and techniques such as cryptography and data encryption could go a long way in risk management.  

Machines and robots that operate on AI models are not immune to cyber hackers. Protecting them from threats is more important than ever. Enhance your organization’s security posture by combining AI with human expertise to improve the results, and stay put in the world of AI.