The first Industrial Revolution used steam and water to mechanize production. The second, the Technological Revolution, offered standardization and industrialization. The third capitalized on electronics and information technology to automate production. Now a fourth Industrial Revolution, our modern Digital Age, is building on the third; expanding exponentially, it is disrupting and transforming our lives, while evolving too fast for governance, ethics and management to keep pace. Most high school graduates have been exposed to information technology through personal computers, word processing software and their phones. Nonetheless, the digital divide separates the tech savvy from the tech illiterate, driven by disparities in access to technology for pre-K to 12 students based on where they live and socioeconomic realities.
Because COVID-19 made it difficult for consumers to venture out and run their usual errands, FIs needed to find other ways to provide their services. The only way for them to really keep up with the speedy digitization was through the implementation of AI systems. To further discuss all things AI, PaymentsJournal sat down with Sudhir Jha, Mastercard SVP and head of Brighterion, and Tim Sloane, VP of Payments Innovation at Mercator Advisory Group. Jha believes that there were two fundamentally big changes that occurred in banking during the pandemic: the environment began constantly shifting, and person-to-person interactions were abruptly limited. "Every week, every month, there were different ways that we were trying to react to the pandemic," explained Jha.
The world's economy is at a tipping point as digital technologies continue to be embedded into both working and personal lives at an unprecedented rate. By 2023, digitally transformed enterprises will account for more than half of global Gross Domestic Product (GDP). Two overarching factors will drive this trend: the proliferation of digital devices and the rising prominence of the millennial and zoomer (Generation Z) user base. These digital-savvy generations account for 75% of the population in the Middle East today. By 2025, the number of connected devices globally is predicted to reach 100 billion, more than 12 times the number of people in this world.
Digital identities are a key component in the development of digital economies, the digital transformation of government, and the delivery of digital operating technologies including the Internet of Things (IoT) and industrial automation. By identifying and authenticating people, software, hardware components, and digital services, new capabilities can be introduced rapidly and securely and integrated into ecosystems, delivering new capabilities using digital identities as a key component of integration.
The news: A new type of attack could increase the energy consumption of AI systems. In the same way a denial-of-service attack on the internet seeks to clog up a network and make it unusable, the new attack forces a deep neural network to tie up more computational resources than necessary and slow down its "thinking" process. The target: In recent years, growing concern over the costly energy consumption of large AI models has led researchers to design more efficient neural networks. One category, known as input-adaptive multi-exit architectures, works by splitting up tasks according to how hard they are to solve. It then spends the minimum amount of computational resources needed to solve each. Say you have a picture of a lion looking straight at the camera with perfect lighting and a picture of a lion crouching in a complex landscape, partly hidden from view.
The federal government has delivered a new digital economy strategy, which it has described as an investment into the settings, infrastructure, and incentives to grow Australia's digital economy. In the strategy on a page [PDF], the government declares the digital economy is key to securing Australia's economic future and recovery from COVID-19. "The Digital Economy Strategy targets investments that will underpin improvements in jobs, productivity and make Australia's economy more resilient," it says. Despite many arguing the nation is already behind its peers, the government believes Australia's place in the world will be defined by how it adapts to digital technologies and modernises its economy. "The next 10 years will determine whether we lead or fall behind," it claims.
KnowBe4, the provider of the world's largest security awareness training and simulated phishing platform, announced a new feature – AI-Driven Phishing. A majority of data breaches begin with a phishing attack and the threat continues to grow. According to the fourth quarter 2020 Phishing Activity Trends Report by the Anti Phishing Working Group, phishing attacks doubled in 2020, growing from 100,000 in January to 200,000 in December. The KnowBe4 phishing platform now leverages machine learning to recommend and deliver informed and personalized phishing campaigns based on users' training and phishing history. Using data from KnowBe4's Artificial Intelligence Driven Agent (AIDA), a new recommendation engine enables admins to automate the selection of unique phishing security test templates for their users.
Cybersecurity experts said that Machine Learning and Artificial Intelligence have positively and negatively affected cybersecurity. Although relatively new AI security tools are often used to define "good" as opposed to "bad" by comparing the behavior of entities throughout the environment with those living in similar environments. Artificial intelligence algorithms are used to train data to respond to different situations. Artificial Intelligence is helping Cybersecurity to accelerate its technological progress. Security experts, including CISOs with products purporting to use artificial intelligence to dramatically improve the accuracy and efficiency speed of both threat detection and response.
Last week, I taught a cybersecurity course at the University of Oxford case. I felt that this is significant because typically the problem domain of AI and cybersecurity is mostly an Anomaly detection or a Signature detection problem. Also, most of the times, cybersecurity professionals use specific tools such as splunk or darktrace(which we cover in our course) – but these threats and their mitigations are very new. Hence, they need exploring from first principles/research. Thus, we can cover newer threats such as adversarial attacks(making modifications to input data to force machine-learning algorithms to behave in ways they're not supposed to).