“The future of AI is not just about creating smarter machines. It is about making technology more accessible and intuitive for everyone,” says Akash Singh, a senior software engineer with eight years of experience in the industry. “We are focusing on integrating AI into security products to help analysts better identify and detect threats while ensuring a seamless user experience.”
As a key contributor to various AI initiatives, Singh helps enhance cybersecurity measures and elevate human-computer interaction in the security domain.
From User Interfaces to Human AI Interactions
Singh’s journey in the tech realm began with a focus on user interface design and accessibility. His master’s thesis, titled “Improving the Usability of Typometric Solutions,” led to the development of a full keyboard-accessible colour picker, allowing users to select from 16 million colours with less than 48 keystrokes.
Building on this experience, his career took him to Belong Home, where he was instrumental in developing innovative solutions for the property management industry. As one of the early hires at the startup, Singh led the development of several ground-breaking features, including an end-to-end digital flow for house rentals and an automated payment system processing millions of dollars annually.
Now at Splunk (Cisco) since December 2023, he has been focusing on integrating Large Language Models (LLMs) into security products. “We are creating an AI assistant for our security products that can help analysts sift through vast amounts of data more efficiently,” Singh explains.
Augmenting Human Decision-Making with AI
One of the key differentiators in Singh’s strategy is the emphasis on user experience in AI systems. “Many AI implementations focus solely on processing speed and data analysis. But I believe that for AI to be truly useful in cybersecurity, it needs to present information in a way that augments human decision-making,” he notes.
This philosophy is evident in the AI assistant Singh is developing at Splunk (Cisco). Early trials have shown promising results, with security analysts reporting significant improvements in threat detection speed and accuracy.
In addition to his work on AI integration, he has made other significant contributions at Splunk (Cisco). He has improved automated testing processes, saving the company an estimated $500,000 annually, and automated local developer environment setup, saving each developer 6-7 hours of setup time.
Building Trustworthy AI Solutions for Security Teams
As Singh and his team push the boundaries of AI technology in cybersecurity, they face a host of challenges, both technical and ethical. Issues of data privacy, algorithmic bias, and the potential for AI to be exploited by malicious actors are at the forefront of these concerns.
“We take these issues very seriously. Every feature we develop goes through rigorous security and ethical review processes. We are also actively working on techniques to make our AI systems more transparent and accountable, allowing security teams to understand and trust the AI’s decision-making process,” he asserts.
The Human-Centric Vision for AI in Security
Singh reflects on the future he envisions for AI in cybersecurity. “The future of AI in cybersecurity is not predetermined. It’s up to us developers, security professionals, and policymakers to shape it. We have the opportunity to create something truly transformative, but we must do so with wisdom, ethical consideration, and a deep commitment to enhancing rather than replacing human expertise.”
From his early work on accessibility to his current role at the forefront of AI integration in security, Singh’s career exemplifies the potential for technology to make a meaningful impact across various domains.
