Illustration by Dorathe Victor Five worthy reads is a regular column on five noteworthy items we discovered while researching trending and timeless topics. In this week’s edition, let’s explore how artificial intelligence and machine learning are weaponized by hackers to fuel cyberattacks. AI and ML are conquering the world at a rapid pace. AI has made life much easier. In many instances, it speeds up manual processes, reduces costs, and eliminates manual errors.

The Russian invasion of Ukraine has triggered an escalation in the number of state-sponsored actors targeting critical infrastructure with DDoS attacks. Criminal syndicates and smaller players are also exploiting the crisis. From fake fundraising efforts for Ukraine to account takeovers and high-velocity bot-driven attacks such as DDoS, BIN attacks, and terminal attacks, cybercriminals are stepping up their own attacks in an effort to benefit from the turmoil.

Now, there’s a loaded question. With so many preceding it: What do we mean by AI? Which aspects of what data are we referring to When it comes to AI? Are ethical practices universal? So, here are a few things to consider.

In the world of cybersecurity, artificial intelligence (AI) has changed the way we discover, respond, and recover from cyberattacks. But despite the several advancements of AI in cybersecurity, cyberattacks are becoming more and more dangerous because of AI. Cybercriminals are now leveraging existing artificial intelligence tools and AI-based technologies for use in their own attacks, and as a result, cyber threats and attacks are becoming harder to prevent.

The impact of AI on cybersecurity continues to be a hot topic of discussion within the information security industry. Cyber-threats are rapidly increasing in volume. In part, this is because the attack surface for cybercriminals is huge, and it continues to grow and evolve at a lightning pace. Every year billions of cyber-attacks are launched with a wide variety of motives, and new threats with more sophisticated tactics or methods are trialed to bypass existing security systems.

Observability has gained a lot of momentum in the past year, be it full stack observability or data observability. Modern complex IT systems using clouds, microservices and serverless are easy to develop and deploy but extremely difficult to observe. These systems generate tremendous amounts of data and need an automated way of handling the volume. The next era of delivering customer experience is underpinned by the full stack observability capability.

Artificial intelligence (AI) is playing an increasingly important role in cybersecurity. This is confirmed by a recent Pulse survey of 191 senior executives from companies on four continents: two out of three organizations (68%) say they are using tools that use AI technologies and among those who are not yet using AI, 67% are considering adopting it.

For years, biotechs have been hampered by the administrative burden of seemingly endless amounts of diverse, siloed data, slow data ingestion, and security threats coming from internal and external sources. And yet, the life sciences industry continues to see double-digit growth. It’s now worth $285 billion a year, with no signs of slowing down.

Artificial intelligence (AI) is reinventing the trajectory of cybersecurity and fighting with a double-edged sword. If harnessed correctly, AI can automatically generate alerts for emerging threats, detect new types of malware, and protect sensitive data. While it has advanced us into a plethora of new technologies -- think Siri, facial recognition, and Google’s search engine -- it has also probed us with significant threats from cybercriminals.