AI is grouped into several categories:<\/h2>\nMachine learning<\/h3>\n
Machine learning is one of the most common, and it\u2019s a leading disruptor in business. It underpins many AI-powered applications by letting people teach computers how to recognize patterns in large data sets. This technology enables smarter business decision-making, as well as helping organizations protect themselves from cyberattacks with sophisticated measures like threat modeling and intelligence<\/a>.<\/p>\n Deep learning is a subset of machine learning. It\u2019s computationally intensive, using advanced artificial neural networks that allow computers to learn from their own mistakes and continually improve their functions, like the way the human brain works. This has profound implications for business automation, reducing human error in critical areas like cybersecurity.<\/p>\n Alternatively, AI is also defined by the system\u2019s level of intelligence rather than its purpose or how it\u2019s deployed. Using this definition, we have three types of AI: narrow (ANI), general (AGI), and super (ASI).<\/p>\n We already interact with ANI daily both in our professional and personal lives \u2013 common examples include personal assistants like Google Assistant, Amazon Alexa or Apple Siri. Some ANIs use natural language processing<\/a> (NLP) to understand speech and interact with people in more meaningful and natural ways.<\/p>\n Next up the hierarchy is AGIs, these are AIs that are approximately as capable as humans<\/a> and able to solve tasks beyond what they\u2019re originally programmed to do, but it\u2019s still an emerging field.<\/p>\n At the final level, we have ASIs, more intelligent than humans \u2013 think Terminator or The Matrix. That\u2019s still quite a long way off.<\/p>\n The law of unintended consequences holds that the intervention of any complex system tends to create unanticipated and sometimes undesirable outcomes. Digital technologies have, in many ways, made our lives easier. Still, they\u2019ve also opened up a raft of new opportunities for criminals, not to mention challenges regarding personal privacy with big tech firms. With much of the power in the hands of organizations, business leaders must think carefully about ethical and legal implications when adopting AI.<\/p>\n While businesses use AI to improve customer experiences and automate a multitude of routine tasks, cybercriminals can use these technologies. We can certainly count on AI not being used exclusively for good.<\/p>\n There\u2019s no denying that AI will transform every industry, including cybercrime. For a start, AI tools are already widely available, and many are open-source, meaning they\u2019re available for free for anyone to use and reprogram for their purposes. The malicious applications of AI are already starting to emerge as cybercriminals use the technology in ways that mimic the practices of legitimate organizations.<\/p>\n Just as marketing departments are tapping into AI for precision targeting at scale, so are social engineering scammers. Other areas of misuse include creating and targeting misinformation campaigns and impersonating individuals through the use of deepfakes<\/a>. AI-driven insights may also help to develop dangerous malware or show insights into vulnerable systems.<\/p>\n Another immediate challenge with the spread of AI comes down to people. On top of concerns that AI will displace many low-paid, unskilled jobs is the fact that people are still holding all the cards. While maintaining control might help prevent AI from going rogue, it also means that systems inherit our less fortunate human traits, as Microsoft found out<\/a> with the embarrassing launch of its AI-powered Twitter bot Tay in 2016.<\/p>\n People are still teaching computers, and, because of that, there\u2019s an innate bias reflecting society\u2019s perceptions. Or, in the case of Tay, the bad influence of social media trolls. Indeed, earlier this years, a new study found that algorithmic bias in self-driving cars<\/a> increased their chances of failing to detect dark-skinned pedestrians.<\/p>\n AI is here to stay. It\u2019s the next step in advancing digital technology, and a growing number of core business processes soon won\u2019t be able to function without it.<\/p>\n For those who believe in using data ethically, AI is a source of hope, but, like any other technology, some will try to misuse it. To keep up with the new wave of threats as hackers exploit AI, businesses need to respond using AI-enabled tools to augment human intelligence and, consequently, strengthen their cyber defenses.<\/p>\nDeep learning<\/h3>\n
Narrow, general and super AI<\/h3>\n
Protect your business from AI-powered attacks<\/h2>\n
![\"cybersecurity](\"https:\/\/media.kasperskydaily.com\/wp-content\/uploads\/sites\/92\/2020\/01\/24065608\/cybersecurity_and_AI_inline-1024x576.png\")
<\/p>\nUsing AI for good<\/h2>\n