It can also reflect human flaws and inconsistencies, including 180 known types of bias. Biased AI is everywhere, and like humans, it can discriminate against gender, race, age, disability and ideology. AI bias has enormous potential to negatively affect women, minorities, the disabled, the elderly and other groups. Computer vision has more issues with false-positive facial identification for women and people of color, according to research by MIT and Stanford University. A recent ACLU experiment discovered that nearly 17 percent of professional athlete photos were falsely matched to mugshots in an arrest database.
In recent years, cybercrime has reached epidemic proportions, with far ranging impacts across the business world. Cyberattacks pose a monumental threat with major developments: attacks have become far more sophisticated and they have exponentially increased in volume. Better executed than ever before, the UN estimates that 80 per cent of all cyberattacks are carried out by technologically-advanced criminal organisations that share data, tools, and expertise. By 2021, it is estimated that cybercrime will cost the global economy over $2 trillion. This makes it imperative for companies to make concerted efforts to improve their cybersecurity health, and evolve from a compliance-focused approach to a more threat-aware strategy focusing on risk.
We've seen inappropriate and unintended bias emerge from various industries' use of AI, including recruiting and mortgage lending. In those cases, flawed outcomes were evident as bias was reflected in ways that relate to distinct features of our identity: gender, race, age. But I've spent a lot of time thinking about areas in which we don't even realize AI bias is present. In a complex field like cybersecurity, how do we recognize biased outcomes? AI has become a prime security tool, with research indicating that 69% of IT executives saying they can't respond to threats without AI.
Experts say Iran may retaliate for the killing of Qassem Soleimani, its top military leader, with cyber attacks on American companies. Experts say Iran may retaliate for the killing of Qassem Soleimani, its top military leader, with cyber attacks on American companies. Cybersecurity researchers and U.S. government officials said hackers linked to Iran are probing American companies for vulnerabilities. The warnings suggest that the next phase of hostilities between the U.S. and Iran, following the Jan. 3 killing of a top Iranian general in an American drone strike, is likely to play out in cyberspace. The Iranian regime is accused of being behind some high-profile online operations against American targets in recent years.
Critical attacks and massive breaches escalated dramatically in 2019 and it is predicted that by the year 2020, costs related to damage caused by cybersecurity breaches may reach $5 trillion. As attacks increase cybersecurity teams are overworked, understaffed, and are grasping for solutions to solve an increasing amount of problems. The current state of AI is begging for a number of problems to be solved in order to continue effectively protecting users from malicious actors. Due to an extreme shortage of cybersecurity professionals, many companies are turning to Artificial Intelligence as a sort of panacea to better defend their networks and make up for a lack of personnel. Another layer of complexity gets added when we consider the false positive or negative problem most security companies have because they are either setting their thresholds too high or too low.