How Artificial Intelligence is Changing the World
Modern Artificial Intelligence systems can capture and ‘understand’ their environment in real-time; they can make optimal decisions, based on multiple signals, in milliseconds. With applications ranging from self-driving cars and digital agents powered by GPT and LLMs, to healthcare and diagnostic systems, Artificial Intelligence is already changing our world.
AI is frequently referenced with marketing or technophobic hype: media typically overstate the capabilities and in some cases, they present dystopias as the long-term outcome of AI.
If we isolate this hype and focus on the progress made throughout recent years, we clearly see several major technological advancements with fascinating, new capabilities. And we can certainly avoid dystopias: under certain conditions, AI will dramatically improve our world and the quality of life.
Artificial Intelligence Defined
A non-technical, short definition of Artificial Intelligence would be:
… the technology that enables systems to encapsulate cognitive functions along with adaptive and learning capabilities — leading to self-improvement.
Modern Artificial Intelligence systems can capture and ‘understand’ their environment in real-time while making optimal, real-time decisions towards specific objectives.
Environment capturing and ‘understanding’ is powered by processing multiple signals and data streams: technologies such as Computer Vision and Natural Language Processing, enable AI systems to ‘understand’ pictures, videos, and natural language (voice or text). The following provides a few characteristic examples.
Computer Vision — algorithms can now ‘see’
This is an astonishing achievement — the ability of a computer to ‘see’ and identify entities, situations, or even stories in photos and videos. Any random image or video can be ‘instantly’ scanned against popular entities (persons, cars, houses, streets, trees, etc.) and possibly with additional context-specific logic.
Moreover, algorithms can estimate additional attributes of the image and properties of the entities identified in it: in the above example, these could include the number of persons in the picture, their gender, age, or even their emotional state; or the type of cars and their brands.
It is also feasible to identify the situation implied in the image or video — such as a kids' party, a sports event, a business conference, or a random arrangement of people in a park.
The possible applications of computer vision are impressive: from autonomous cars that can ‘see’ in 360 and understand their environment and its dynamics in real-time, to special applications like the Seeing AI by Microsoft — a prototype system helping people who are visually impaired or blind to understand their environment.
In the latter example, the user could ask for a detailed description of the surrounding space or for updates on changes; the response could then be provided as a description in natural language via a synthesized voice.
Navigation systems, robotics, medical examination, online content management, and security systems are just some indicative areas of applications powered by Computer Vision.
The dialogue with the ‘machine’
A short interaction with Amazon Alexa, Cortana, Siri, or Google Assistant, is sufficient to realize the huge progress of Natural Language Processing technologies.
Microsoft and IBM report that their NLP technologies perform at the same level (or better) compared to professional transcribers in processing discussions of various topics. Although NLP algorithms may still have difficulties with different accents and noisy environments, their overall performance is improving fast.
Interaction with Digital Assistants expands from ad-hoc ‘question and answers’ scenarios to ‘natural dialogues’. Digital Assistants are getting smarter — powered by the wealth of data available for the users and their environment;
Digital Assistants will soon act autonomously — for example by initiating a meaningful discussion that is triggered by non-obvious logic applied to signals from the user’s environment and the deep knowledge the system has for the user and his/her implied or explicitly statedpreferences.
Your Digital Assistant will soon ask you ‘random’ but surprisingly meaningful questions; it will make timely suggestions regarding social, informational, educational, scheduling, and traveling activities of your interest.
Most importantly, it will learn and self-improve according to your engagement levels and other patterns of your lifestyle.
The value of AI and the concerns
The progress in Artificial Intelligence technologies along with the expanding capabilities of handling and processing massive volumes of data drives this major technological revolution we are about to experience.
In the context of the Internet of Things (IoT), billions of connected devices will be sending events, operational and other data, that will be stored and processed by advanced Big Data, Machine Learning, and Artificial Intelligence technologies.
This wealth of data, combined with the increasing ability to automatically make sense of it, will create unprecedented opportunities for improvement across health, lifestyle, transportation, education, and practically every human activity.
On the other hand, there are serious concerns and unanswered questions regarding possible social, political, and ethical implications. For instance, the ‘intelligent automation’ which can be achieved at scale by using Artificial Intelligence, is expected to transform the way we work and the skills in demand: as tasks will gradually become fully automated, roles will become obsolete and some professions will eventually disappear.
Other voices, raise issues regarding ‘who has access and control’ over the accumulated data, the derived knowledge and the power provided by Artificial Intelligence.
Getting ready for the AI revolution
The technological revolution is here and it is already transforming our world.
People need to get ready, first by understanding the technology, its potential, and the associated risks; then by entering a life-learning mode to acquire new skills and explore new talents that are more relevant to the new market order.
States must understand the new dynamics and adapt by modernizing laws, frameworks, social programs, and the education system.
Thought leaders need to introduce the right rules and global agreements to avoid the centralization of power and control over data and technology.
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