2020 has been a boon for bad actors looking to exploit our larger online footprint. While the global pandemic expanded the many ways in which we live, work and learn online, hackers are leveraging this broadening digital engagement to their advantage. Since January, there has been a 400% jump in cyber attack reports to the FBI Cyber Division. Just last week we saw a crippling incident where hackers attacked the United Nations shipping regulation arm and the International Maritime Organization (IMO). Several pharmaceutical clinical trials were also hit by ransomware attacks.
In response, an estimated 83 percent of enterprises report transforming their approach to cybersecurity in 2020, accelerating migrations to the cloud and integrating automation and artificial intelligence (AI) tools. However, there remains a shortage in cybersecurity talent and a growing skills gap globally. Security budgets, including US federal cybersecurity funds, are insufficient to keep pace with the US $6 trillion in cybercrime damages predicted in the United States for 2021.
To combat growing sophistication from attackers, enterprises are turning to AI solutions that are able to detect abnormalities in real time. These tools can oversee the many contact points where an attacker may try to enter, alter, or extract data from a system. These models will also catch vulnerabilities in code before the application’s launch by running scans and reinforcing Security-by-Design principles. As enterprises introduce AI-based solutions, security analysts’ focus will shift from monitoring and triaging alerts to problem-solving and communicating security issues.
However, as with any game of cat and mouse, bad actors will look to leverage defensive tools to exploit weaknesses. AI models may become a target if training data and pipelines are not protected. We expect constant innovation in this sector and broadening applications of AI as enterprises keep pace with the growing sophistication of those looking to undermine our digital capabilities, and are actively looking at disruptive startups in this space.
AI and deep tech headlines for the week of October 26, 2020
When Do We Trust AI’s Recommendations More Than People’s? (Harvard Business Review)
Consumers may prefer AI recommendations to human ones. “Word-of-machine” effect suggests people will defer to machines when it comes to functional and practical aspects of a product.
AI is about to face a major test: Can it differentiate Covid-19 from flu? (STAT News)
With COVID cases surging at the same time as the seasonal flu, AI models may be used to sift through data on symptoms, chest X-rays and CT scans to aid in diagnosis. AI may also be called upon by healthcare workers to determine how aggressively they should treat patients during flu season.
Invest Ottawa Receives $17 Million to Expand Autonomous Vehicle Test Facility (Betakit)
This facility will help the innovation community develop, test, commercialize, and export solutions across a number of high-growth global markets, including smart mobility.
Facebook’s new AI can translate languages directly into one another (Engadget)
Facebook AI has developed a new model that can bidirectionally translate directly between two languages without ever using English. This novel approach outperforms standard English-centric models.
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