Today, our technological progress has reached far off; we have been inventing machines that seem to act like humans. Yes, that’s correct, Artificial Intelligence. Before moving on too far away, let’s get some clarity on what is Artificial Intelligence. In simple terms, Artificial Intelligence has the power to replace Human Intelligence. They are nothing but machines. These machines are powered by intense learning and following the protocols.
This article will throw some light on what are the benefits of AI, and what risks it engenders. It will mainly focus on the security hack, which could be detrimental to humans.
Our great scientists have progressed rapidly right from inventing SIRI to Self-driven cars. Artificial Intelligence is termed as Narrow AI today, with its limited abilities. However, our scientists have a great vision. They are yet to come up with General AI. Narrow AI, with its limitations, might still outperform humans at any task; however, with General AI, it is sure to beat humans at any cognitive task.
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As said and heard, everything comes with a price. With AI progressing in myriad fields these days, there is a risk of Artificial Intelligence getting hacked. They have been doing this since ever now with the invention of technology. It is only a matter of time before they will cut through these intelligence systems.
It is quite challenging to get hold of these hackers. Because it seems that no matter how efficient we are, they have outgrown our smartness, cybersecurity has some massive problems to deal with when it comes to solving the issues of hack and ensuring security.
To ensure safety, Artificial Intelligence Development companies need to roll up their sleeves and become more proactive. They have advanced security in place to deal with Advanced Persistent Threats (APTs) and other related threats; thus, they become confident than ever, and lay relaxed, thinking everything is safe and sound, only to discover it is not. Such an attitude is a surety that they will get hacked.
Smugness can be detrimental sometimes, and it is the case in this scenario. There have been a few questions raised like, How will these AI Development companies put proper security in place while fostering their businesses? Should they have audit facilities to answer regulatory questions?
Do data scientists guarantee the reliability of AI models? How do developers deliver high-quality software for AI software development? Asking the right set of questions can help to understand the problems more clearly.
To gain more advancements, AI Development companies are looking for investment funds to manage and supervise AI, to grow more into the MLOps and ModelOps that will fit into their existing systems. However, the problem is that these companies are not showing that sincerity to combine a machine learning model into the current production environment, which can help make better business decisions. The same goes for AI security. They are still stuck in complexities to direct their AI management team, thus pushing the problems down the road, leading to more trouble in the future.
Deeper Problems to Look at:
The AI system is vulnerable to the attack surface, where the data can get easily extracted from the system. Here, the MLOps comes into the picture. These tools can help the AI development companies stop the access into the AI that’s been used by the data science company, not just that; these tools can help with API threats. Simultaneously there are other threats to look for that poses a risk to the security, which are neglected by the AI Development companies.
There is a term called Adversarial AI, which is a technique of deceiving the AI model by injecting wrong data, in turn, disturbing the patterns, thus causing damage to the AI model. This breach caused by such cybercriminals. Once breached, they can reverse the functioning and thus poison the data, and what could happen is beyond our imagination.
Imagine you are driving a self-driven car that gets tricked into reading the stop sign into 60 Mph sign. Now, you think of what can happen; this is a sheer example of data poisoning.
These cybercriminals use another technique wherein they inject such signals and processes which display no effect on the system. Instead, they train these models into thinking that as healthy. Once they get trained with it being normal, the hackers use this technique to carry out further attacks, because these models get trained to believe that this functioning is normal.
However, don’t worry, there are systems in place to manage such problems. Only a few app developers are devoting their time and funds to look into the security aspects.
Adversarial Defence needs to be a top priority. Otherwise, it is like keeping your cars unlocked for inviting thefts.
Light on Shadow AI:
Okay, so now we about the threats that come from outsiders, but what about insider threats.
Many teams are working on AI within the organization and are on the constant race for bringing in more innovation. And if they can’t seek what they are looking for, they produce it or procure it. However, you can’t function or secure when you are unaware.
The use of AI-related tools and services in place used by individuals without having the technical know-how to develop their AI-powered solutions refers to as Shadow AI. As per the study, 40% of funds consumption takes place by IT departments outside their companies. When this takes place, serious security gaps can engender.
So, How do you address these problems?
This can minimize by generating collective awareness to maintain the security in the organization and work wholly as a team. As mentioned earlier, about the MLOps and the ModelOps, which can help pivot the AI functionings, making it smoother to manage and supervise it in the long term. Lastly, having a constant sight on who is using the AI, and thus taking things under control.
Hence, before the situation goes haywire, make sure of placing proper tools in place. Artificial Intelligence can do wonders and can make human life smoother, provided crucial emphasis in the area where security concerns.