The rise of robo-huntersBlog
How artificial intelligence will reshape the cybersecurity landscape
Internet TV series like Westworld and Black Mirror are enthralling but also disturbing because the scenarios are real possibilities, based on emerging capabilities of Artificial Intelligence (AI). Can AI really get smarter than us, feel emotions like us, take control of environments, and even change what it means to be human?
While we’re a long way from autonomous cyborg creatures, AI is with us today, reshaping the way we live, play, and work – think of Facebook tagging faces, Spotify generating your playlist, Siri answering questions. These are all ubiquitous AI applications.
AI technologies make up a ‘central nervous system’ of capabilities, and their evolutionary path is like our own cognitive development – we progress from sensing, perceiving, and learning, to assimilated knowledge, foresight, and wisdom. While the future of AI brings science fiction into reality, it is continuously maturing in the present.
AI isn’t the future of business, it’s the here and the now.
Learning through recognition
The first stage of AI evolution, perception, refers to the idea that we can only learn from what we recognise. Advances in computer vision and learning have enabled granular recognition, pattern matching and classification of text, voice, 3D imagery, video and VR content, allowing the vast world of big data to be understood.
An example of this is Google Translate – a text-based language translation engine, at first it was inaccurate because it translated word by word, without context of the language. It progressed to analysing whole sentences for meaning, which became the Google Neural Machine Translation (GNMT). GNMT now translates over 100 languages and is maturing its range to translate photo and video images, handwriting, and speech. It’s core AI, now embedded in web browsers, websites, and Google Home, and also used by software developers to create multilingual applications.
In Japan, NTT R&D are developing similar forms of AI to enhance the visitor experience for the 2020 Olympics. 3D visual recognition technology can identify an object from any position, by inferring its 360 degree appearance, and additional technology translates images, such as metro train maps, into multiple languages.
Artificial general intelligence
Artificial general intelligence builds on the core AI perception skills to enable deeper machine learning and at scale, whereby machines connect to share data, make decisions, and act. Based on algorithms, this enables the operation of autonomous or semi-autonomous systems. An extension of this is reinforcement learning, where cumulative analysis of outcomes improves the range and performance of algorithms. We’re bringing this form of AI into our lives via Google Home and Amazon Alexa, allowing them to listen, converse, and become task workers for us.
It also impacts the sports world. At this year’s Tour de France, our IoT, big data and machine learning platform ran algorithms across live and historical race data, to provide extensive performance insights across the event, predicting likely outcomes of riders in real time, which improved the viewers’ experience and engagement.
Artificial super intelligence
Machines have perfect recall, analyse vast amounts of information, and exercise consistent objective reasoning, so they’ve gained an IQ edge over the most gifted humans in some discrete type of logical reasoning (Fritz and chess, Watson and Jeopardy, Deepmind, and AlphaGo). But overall, AI doesn’t yet surpass the blended IQ and EQ (scientific, general wisdom, creativity, and social skills) of a fully developed human. EQ is the next frontier of AI research.
Our relationship with machines is becoming more nuanced and personalised by the day.
Unfathomable computational capacity will be available – in our pockets
Within 10–15 years, we’ll carry supercomputer devices in our pockets. Computing methods such as quantum and neuromorphic will explore questions in time, space, and infinity that aren’t even conceivable today. This will be truly exponential for AI, imagine these approaches applied to resolving climate change impacts or Alzheimer’s disease.
What will AI deliver in the near-term?
A compelling near-term case for AI deployment is for cybersecurity. Until recently, we’ve relied on human security analysts to monitor systems, analyse threats, and act. But there aren’t enough cyber experts in the world to keep up with the changing global threat landscape and rise of cybercrime.
The AI-enabled cybersecurity landscape is actively aware and alert to changes, recognising new patterns as they emerge, modelling likely scenarios, intervening, analysing outcomes, and generating new counter-response capabilities.
This year you may see the rise of ‘robo-hunters’; AI-enabled bots who scan changes in an organisation’s environment that could indicate potential threats. They’ll learn from their discoveries and take appropriate action, such as isolating a compromised device. This will enable more businesses to move from a proactive to a predictive security posture.
This period of AI evolution is pivotal in our relationships with machines, our physical and digital worlds are enmeshed – the interfaces are becoming our clothing, glasses, implants, voices, gestures, and even feelings. We’ve embraced this in daily life and soon our reliance on AI will become the norm at work as well.
More than ever, this is predicated on deep trust and such trust needs to be continuously affirmed and legitimised by the relentless application of AI to cybersecurity. This way, the future is under our control, AI in service of ‘humanity’.
Suddenly, Hollywood’s futuristic dream doesn’t seem so far from reality.
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