Artificial intelligence (AI) has permeated every sphere of our civilization and way of life over the past ten years.
It’s difficult to deny its impact on everything from chatbots and virtual assistants like Siri and Alexa to automated industrial gear and self-driving cars.
Machine learning, which consists of sophisticated software algorithms designed to perform a single specific task, such as answering questions, translating languages, or navigating a journey, and get better at it as they are exposed to more and more data, is currently the technology most frequently used to achieve AI.
According to IDC research, governments and businesses would spend more than $500 billion on AI technology globally in 2023.
But what effect will it have and how will it be used?
The Ongoing Democratization of AI
Only once AI is widely accessible and everyone can use it to their advantage will it realize its full potential.
Thankfully, this will be simpler than ever in 2023.
Regardless of one’s level of technical expertise, a rising number of apps put AI capability at the fingertips of everyone.
This can be as basic as apps that let us build complex visualizations and reports with a click of the mouse, decreasing the amount of typing required to search or write emails.
Due to the increasing availability of no-code and low-code platforms, it is becoming easier than ever to design your own software if one that fulfills your needs is not already available.
These make it possible for almost anyone to develop, test, and implement AI-powered solutions utilizing straightforward drag-and-drop or wizard-based user interfaces.
Examples include Akkio, which can construct prediction and decision-making tools, and SwayAI, which is used to develop enterprise AI applications.
In the end, the democratization of AI will make it possible for companies and organizations to overcome the difficulties brought on by the AI skills gap caused by a lack of qualified data scientists and AI software engineers.
The potential and value of artificial intelligence will be accessible to all of us by enabling anybody to become “armchair” data scientists and engineers.
Generative AI
Most people would likely respond that the primary application of AI is to automate monotonous, routine jobs if you ask them what they believe AI to be beneficial for.
Although this is frequently the case, a growing field of science is devoted to creating AI tools and programs that can emulate creativity, one of the skill sets that is most distinctively human.
The utilization of existing data, such as video, photos, sounds, or even computer code, by generative AI algorithms results in the creation of wholly new content that has never been in the non-digital world.
GPT-3, designed by OpenAI, is one of the most well-known generative AI models. It is capable of producing text and prose that are almost identical to human-written text and writing.
Images are produced using a GPT-3 variation called DALL-E.
Thanks to experiments like the well-known deepfaked Tom Cruise films and the Metaphysic act, which dominated this year’s America’s Got Talent, the technique has gained widespread attention.
But by 2023, we’ll see it utilized more regularly to generate fake data that organizations can use for a variety of things.
The necessity to record film and speech on video can be eliminated by synthetic audio and video data; just type what you want the audience to see and hear into your generative tools, and the AI will produce it for you!
Ethical and Explainable AI
For these reasons, it is crucial to create AI models that are more moral and comprehensible.
But the most important factor is trust.
AI needs data to learn, and this data frequently consists of personal information.
This might be extremely private data, such as health or financial information, for many of the most valuable and potent AI use cases.
The entire system collapses if we, the general public, don’t feel comfortable sharing our information and don’t comprehend how AI makes decisions.
There will be initiatives to solve the “black box” issue with AI in 2023.
Those in charge of installing AI systems will exert more effort to make sure that they can clearly communicate how judgments are made and what data was utilized to reach them.
As businesses learn how to remove bias and injustice from their automated decision-making systems, the role of AI ethics will also grow more important.
Biased data has been demonstrated to cause prejudice in automated outcomes, which has the potential to result in discrimination and unfair treatment. This is inexcusable in a world where AI influences decisions about access to work, justice, and healthcare.
Augmented Working
More of us will be working with robots and intelligent machines in 2023 that were created particularly to assist us in performing our jobs more effectively.
This might take the form of smart phones that provide us with rapid access to data and analytics tools, as we have seen them employed more and more in industrial and retail industries.
It could refer to headsets with augmented reality (AR) capabilities that project digital information over the real world.
This could provide us with real-time information that can assist us identify dangers and threats to our personal safety in a maintenance or manufacturing use case, such as pointing out when a wire is likely to be live or a component may be hot.
Access to real-time dashboards and reporting, which provide an immediate up-to-the-minute picture of operational effectiveness, will be made more widely available to management and leadership teams.
AI-powered virtual assistants, who can rapidly respond to inquiries and automatically offer different, more effective ways to achieve goals, will also become increasingly common in the workplace.
In general, learning how to collaborate with and work alongside clever, smart machines will become a more valuable work skill. Even so, I’d venture to argue that it will significantly lessen the risks of our roles becoming obsolete for many of us.
Sustainable AI
All businesses will face pressure in 2023 to lessen their environmental impact and carbon footprint.
In this regard, the rush to embrace and monetize AI has the potential to be both advantageous and detrimental.
AI algorithms demand a growing amount of power and resources, as does the infrastructure required to support and deliver them, such as cloud networks and edge devices.
In a 2019 study, it was discovered that training a single deep-learning model may release 284,000 kilos of CO2.
At the same time, by locating areas of waste and inefficiency, the technology has the ability to assist businesses in comprehending how to create goods, services, and infrastructure in a more energy-efficient way.
The aim to deliver more sustainable AI includes ongoing efforts to develop infrastructure that is fueled by more green and renewable energy sources.
