Elevate Your Tech Career With the Best AI and Machine Learning Courses

Mar 30, 2024 • 9 min read

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Artificial Intelligence (AI) and machine learning are two of the fastest-growing emerging technologies right now. In late 2022, generative AI burst onto the tech scene in the shape of ChatGPT and its antecedents. However, that’s not the first time AI has made a major impact. In fact, the first AI chatbot, Eliza, was around in the 1960s.

Both AI and machine learning do far more than chat and research. AI is embedded in analytics, predictive forecasting, and monitoring for multiple industries. As the use of AI and machine learning expands, the need for professionals with relevant skills is also growing exponentially.

OPIT (Open Institute of Technology) provides top-tier education in various tech fields, including highly respected machine learning and artificial intelligence courses. Let’s take a look at these fascinating technologies and how the right AI machine learning course can elevate your tech career.

Understanding AI and Machine Learning

When you’re searching for courses on artificial intelligence and machine learning, it helps to have a basic definition for both terms. If you already work in the tech industry, you likely work with one or both of these technologies every day. Yet they’re often so embedded within systems or apps that you might not even realize.

AI refers to the computer’s to exhibit behavior that replicates human thought patterns. However, the details of this definition are a little more complex than that. “Computers” can mean anything from a small subsystem to a supercomputer. It can also mean your smartphone or an app. And, by emulating human behavior, experts don’t necessarily mean AI does things exactly like us. Truly “thinking” AI with genuine cognitive abilities is a long way off.

What AI actually does is take things humans can already do – and do it faster and more often. Think about a software DevOps team requiring automated monitoring and testing of code prior to deployment. AI can do this while checking for vulnerabilities and producing relevant, actionable reports. In healthcare, AI uses pattern recognition to diagnose diseases quickly.

Machine learning is a subset of AI. It focuses on using algorithms to consistently and continuously improve pattern recognition for AI that appears to “learn.”

Courses in AI and machine learning are so popular because of the inherent usefulness of these technologies. Learning these skills now is a way to future-proof your tech career.

The Best AI and Machine Learning Courses

Numerous artificial intelligence and machine learning courses cover different topics and niches. You may choose to learn in a classroom setting or remotely. Some courses are short-term, generally covering foundational aspects of AI. Others carry on over several months for a deeper learning experience. Always consider how the course you invest in will impact your career advancement opportunities.

Absolute beginners may benefit from the Coursera IBM Applied Professional Certificate. This course runs entirely online over three months, presuming you can commit to 10 hours a week. Students learn the basics of AI, particularly how it powers IBM’s Watson AI services.

Oxford Online runs a 6-week online AI program course requiring 7-10 hours of commitment a week. This course looks at AI concepts and business cases for implementation and takes a glimpse at the future of AI.

For classroom-based courses on AI and machine learning, prospective students are best placed to contact local educational institutions. Offline courses vary in length, depth, and usefulness, so always check the syllabus and what certification you gain. It’s worth considering how far you’ll have to travel to gain a qualification.

One of the biggest challenges with AI is making it ethical. OPIT addresses that head-on with the MSc in Responsible AI. Learn advanced AI skills while keeping inclusivity and human interest at the heart of every aspect of the syllabus.

OPIT also offers other courses that consider the impact AI has on modern business practice. Undergraduates could consider the BSc in Digital Business, which includes a full Introduction to AI segment. There are also elective topics, including AI-Driven Software Development.

The Structure of AI and Machine Learning Courses

What should you expect from the best courses on AI and machine learning? Each course has a specific length, either in terms of study hours or a set deadline date. Most online courses have a specific intake date to make sure students get the right support at the right time.

Once you start your machine learning and AI course, you can expect a good balance between theory and practical application. For example, OPIT’s master’s degree course starts with foundational theory and critical thinking around ethics in AI. From here, students get to handle complex data sets. They program in Python and learn how to design effective AI-powered data pipelines.

The structure of your course will depend on the focus, but to give you the best foundation, courses may follow a similar pathway to this:

Basics of AI, including the differences between AI and machine learning
Discovering applications of AI — these may be general or industry-specific, depending on the nature of your course
Data collation, analysis, and visualization
Programming for AI
Natural language processing (NLP) and natural language generation (NLG)
Removing or preventing bias in AI training

Some courses will also offer advanced elective programs, such as understanding AI within the sphere of FinOps (financial operations) or business strategy. If you have a particular industry you’re hoping to excel in, look out for courses with topics that could help you further those ambitions.

Online AI and Machine Learning Courses: Flexibility and Accessibility

Choosing one of the best machine learning and AI courses to do online offers more benefits than new skills. Online learning allows you to study in your preferred environment and at your own pace. You just need to make sure you keep an eye on set deadlines.

You’re not distracted by a class full of people, but you still have access to tutors and support. Many open learning institutes have online communities of students. These are great for preventing isolation and gaining advice.

As a tech professional, the ability to set your own study schedule is essential. Online AI and machine learning courses provide flexibility, allowing you to learn as you work. With OPIT’s Master’s Degree in Responsible Artificial Intelligence, you could potentially have an MSc in 12-18 months without taking any time off work.

Key Skills Gained from AI and Machine Learning Courses

When choosing your online course on AI and machine learning, consider the skills you’ll learn. You should expect to cover:

Data preprocessing
Data cleansing
Data visualization and storytelling
Linear and nonlinear dimensionality reduction
Manifold learning
Human-centered AI design
Language-agnostic AI programming skills

An MSc in AI and machine learning provides specialized skills and knowledge that you can use to address complex AI challenges in just about any industry.

Choosing the Right AI and Machine Learning Course for You

Picking the right AI and machine learning course is simpler when you consider your goals. Do you want a quick upskill and insight into emerging technologies? Or do you want an immersive course that empowers you to take on new career challenges? Most AI and machine learning courses will provide guidance on the type of career students could hope to pursue after completion.

Always look at the syllabus of a course and see if it meets your personal goals. If you’re unsure about any aspects, contact the education provider for more information.

OPIT’S MSc in Responsible Artificial Intelligence: An Overview

If you’ve decided an online AI and machine learning course is for you, as a graduate, an MSc is the natural choice. The next intake for the OPIT MSc in Responsible AI is September 2024, and details on how to apply are online.

What are the benefits of taking this course?

A fast-track option to gain your master’s degree in just 12 months
Fully inclusive fees — no hidden charges
Various scholarship and funding options
Availability of early-bird discounts
Access to academic leaders from all over the world
Education with an EU-accredited institution

Your MSc course covers every aspect of AI you might require for a career in AI and machine learning. Topics start with AI and ethics and quickly move into human-centered design, computer vision, and how AI impacts IoT and automation.

As you move into your final term, you start your MSc thesis, which focuses on AI projects with industrial relevance. There’s also the opportunity to pursue an internship to complement your thesis and gain vital experience.

AI and Machine Learning Courses for a Future-Proof Career

AI is now part of most growing industries, from property and real estate to healthcare and social care. Tech professionals have the opportunity to upskill themselves and move into fields that they have a real passion for. Organizations are looking for and willing to pay high salaries for knowledgeable, qualified AI experts.

Taking the time now to embark on machine learning and AI courses could speed your journey along your chosen career trajectory.

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From the same author
Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
OPIT - Open Institute of Technology

April 14, 2025
Source:
- Il Sole 24 Ore, published on April 14th, 2025
Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI Act and to guide companies towards a path of regulated adoption of the technology.

“CEOs who already work with AI – explains the OPIT expert – see the investment in compliance as necessary, the latter as an opportunity: and the latter, on paper, have the advantage of being able to define a strategy also in terms of ethics and civil responsibility”

SMEs in greater difficulty

There is a further theme that accompanies the diffusion of AI in the European corporate fabric and that is the difference in “approach” between large companies and SMEs. The top executives of enterprise-class organizations, as Casale confirms, have budgets and resources to adequately address and manage the challenge of compliance. Small and medium-sized businesses, on the other hand, are in a waiting position to understand how to carry forward the development process and the risk that many may slow down in the innovation path, and that a conservative attitude towards the use of artificial intelligence prevails, is clear.

Lastly, no less important is the issue of skills, which is very much felt in both the technical and legal fields. “The skills and requirements of AI Engineers and Data Scientists, with all their variations on the theme, are now defined and it is clear – Casale assures – that there is a strong increase in demand. However, I am of the opinion that there cannot be training that is only engineering-based or focused solely on regulatory aspects: instead, we need paths that combine the two dimensions and that lead to preparing the new Chief AI Officers, that is, high-level responsibility figures called to govern all activities related to the use of artificial intelligence”. Nonetheless, according to the expert, we need a layer of specialists who study the impacts and implications of technology on society, anticipating possible risks.

Old universities are not enough

In conclusion, it remains to be asked whether Italy is up to speed in meeting this need, and in this regard Casale’s answer is once again precise and transparent: “Old-style universities can no longer be functional for this purpose, because we need to understand how to teach a new mindset and not a technology as such, given the speed of its evolution. We are in the midst of a phase of great change and evolution towards dynamic study paths, and in other European countries this transformation has already begun”. In the meantime, artificial intelligence continues on its course and suggests that it will not be a passing fad. On the contrary. “AI – concludes the OPIT professor – exists and is here to remain a protagonist: to teach it and bring it to the ground in an adequate way, correct governance of the technology is necessary and the AI Act is an important first step in this direction. But there is still a lot of work to do”.

Read the full article below (in Italian):
- Il Sole 24 Ore
Check out OPIT degrees

BSc in Digital Business MSc in Digital Business and Innovation MSc in Responsible Artificial Intelligence MSc in Applied Data Science and AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI
- Career aligned
- Fully Online
- EU-accredited institution
Read the article
The Lucky Future: How AI Aims to Change Everything
OPIT - Open Institute of Technology

April 10, 2025
There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

How AI Aims to Change Everything

For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:
- Where we are currently with AI and future trajectories
- The impact AI is having on the job landscape
- Sustainability concerns and ethical dilemmas
- The fundamental risks associated with current AI technology
According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

Industry Applications of AI

While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

The AI Revolution and the Job Market

According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

Is AI Sustainable?

While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

Risks of Using Generative AI

While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.
- Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
- Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
- Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
- Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
- Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
- Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.
Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

A Lucky Future

Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.
Check out OPIT degrees

MSc in Digital Business and Innovation MSc in Responsible Artificial Intelligence MSc in Applied Data Science and AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI
- Career aligned
- Fully Online
- EU-accredited institution
Read the article
Categories
Authors

Francesco Profumo

John Loewen

Professor @OPIT, PhD in Computer Science, Former Professor @Chulalongkorn University and @Vancouver Island University. Location: Italy Teaches Computer Architectures (BSc).

Karim Bouzoubaa

Professor @ OPIT, Professor of Data Science & AI @ Mohammed V University in Rabat, PhD @ Laval University. Location: Canada, Morocco. Teaches Programming courses (BSc).

Khaled Elbehiery

Professor @ OPIT, Senior Director & Network Engineer @ Charter Communications, Professor @ DeVry University and @ Park University. Location: USA. Teaches: Computer Networks (BSc).

Lokesh Vij

Professor @ OPIT, Software Engineer @ Symantec, Faculty @ Seneca College. Location: Canada. Teaches Cloud Computing courses (BSc), Big Data and Cloud Computing Infrastructure (MSc).

Go to all authors

Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management

OPIT - Open Institute of Technology

Apr 14, 2025 • 6 min read

Source:

Il Sole 24 Ore, published on April 14th, 2025

Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI Act and to guide companies towards a path of regulated adoption of the technology.

“CEOs who already work with AI – explains the OPIT expert – see the investment in compliance as necessary, the latter as an opportunity: and the latter, on paper, have the advantage of being able to define a strategy also in terms of ethics and civil responsibility”

SMEs in greater difficulty

There is a further theme that accompanies the diffusion of AI in the European corporate fabric and that is the difference in “approach” between large companies and SMEs. The top executives of enterprise-class organizations, as Casale confirms, have budgets and resources to adequately address and manage the challenge of compliance. Small and medium-sized businesses, on the other hand, are in a waiting position to understand how to carry forward the development process and the risk that many may slow down in the innovation path, and that a conservative attitude towards the use of artificial intelligence prevails, is clear.

Lastly, no less important is the issue of skills, which is very much felt in both the technical and legal fields. “The skills and requirements of AI Engineers and Data Scientists, with all their variations on the theme, are now defined and it is clear – Casale assures – that there is a strong increase in demand. However, I am of the opinion that there cannot be training that is only engineering-based or focused solely on regulatory aspects: instead, we need paths that combine the two dimensions and that lead to preparing the new Chief AI Officers, that is, high-level responsibility figures called to govern all activities related to the use of artificial intelligence”. Nonetheless, according to the expert, we need a layer of specialists who study the impacts and implications of technology on society, anticipating possible risks.

Old universities are not enough

In conclusion, it remains to be asked whether Italy is up to speed in meeting this need, and in this regard Casale’s answer is once again precise and transparent: “Old-style universities can no longer be functional for this purpose, because we need to understand how to teach a new mindset and not a technology as such, given the speed of its evolution. We are in the midst of a phase of great change and evolution towards dynamic study paths, and in other European countries this transformation has already begun”. In the meantime, artificial intelligence continues on its course and suggests that it will not be a passing fad. On the contrary. “AI – concludes the OPIT professor – exists and is here to remain a protagonist: to teach it and bring it to the ground in an adequate way, correct governance of the technology is necessary and the AI Act is an important first step in this direction. But there is still a lot of work to do”.

Read the full article below (in Italian):

Il Sole 24 Ore

Read the article

The Lucky Future: How AI Aims to Change Everything

OPIT - Open Institute of Technology

Apr 10, 2025 • 7 min read

There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

How AI Aims to Change Everything

For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

Where we are currently with AI and future trajectories
The impact AI is having on the job landscape
Sustainability concerns and ethical dilemmas
The fundamental risks associated with current AI technology

According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

Industry Applications of AI

While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

The AI Revolution and the Job Market

According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

Is AI Sustainable?

While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

Risks of Using Generative AI

While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

A Lucky Future

Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.