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Travelling fast on the bumpy road of AI

The lecture below, provided in video and text, was originally held at a conference in South Korea held by Business Sweden.

Ladies and gentlemen, welcome to today’s presentation titled “Traveling Fast on the Bumpy Road of AI.” My name is Carl Heath, and I am a senior researcher at RISE – Research Institutes of Sweden. I have a background in the fields of applied IT, education and innovation, and have been exploring the application of AI in various contexts over the past years. I am excited to share with you some insights and knowledge on this rapidly evolving technology!

In this presentation, we will explore various aspects of AI, from its basic principles and the latest developments to its applications across diverse sectors, such as education, healthcare, and business. We will also delve into the challenges and ethical considerations related to AI, addressing the balance between opportunities and risks.

Our journey together will touch upon AI and research, strategies for adoption, and the importance of collaboration and dialogue among stakeholders. As we navigate the fast-paced and sometimes bumpy road of AI, we will gain a better understanding of how to harness its potential responsibly and ethically, ensuring that this transformative technology benefits society as a whole.

So, without further ado, let’s embark on our journey through the fascinating world of artificial intelligence!

What is AI?

AI is a transformative technology that mimics human intelligence, enabling machines to learn, reason, and solve problems in ways similar to us.

A key feature of AI is its ability to process vast amounts of data. AI algorithms sift through this data, identifying patterns and making predictions that would otherwise be too complex or time-consuming for humans. This data-driven approach is essential in powering AI’s capabilities and potential applications.

One of the most significant benefits of AI is its ability to enhance decision-making. AI systems can analyze complex situations, offering solutions based on data analysis and pattern recognition. This improves efficiency and accuracy, allowing for better, more informed decisions across various sectors, from healthcare and finance to education and sustainability.

AI is a powerful technology that mimics human intelligence, relies on data processing, and improves decision-making. As AI continues to evolve and shape our world, it offers incredible opportunities for innovation and progress, touching every aspect of our lives.

Examples of AI technologies

Let me break down some key examples of AI technologies: machine learning, deep learning, natural language processing and Large Language Models.

First, let’s talk about machine learning. In a nutshell, machine learning is a method that allows computers to learn from data, improving their performance over time without the need for explicit programming. Imagine a computer program that gets better at recognizing images of cats as it analyzes more and more cat pictures – that’s machine learning in action!

Next, we have deep learning, which is a subfield of machine learning. Deep learning uses artificial neural networks, inspired by the human brain, to process and interpret complex data. This technology has been instrumental in advancements like facial recognition, self-driving cars, and even AI-generated art.

We also have the field of natural language processing, or NLP. NLP focuses on enabling computers to understand and interact with human language. This technology is behind applications like voice assistants, automated customer support, and language translation software. NLP allows us to communicate with AI systems using our own language, making them more accessible and user-friendly.

LLMs, or Large Language Models, are a prime example of the intersection of the three AI technologies we discussed earlier: machine learning, deep learning, and natural language processing. LLMs are the foundation of AI services such as chatGPT, that is have been hard not to engage in over the past months.

First, machine learning serves as the foundation for training LLMs, as they learn from vast amounts of text data to generate human-like language. The models continuously improve their understanding and performance as they are exposed to more data.

Second, deep learning plays a significant role in LLMs through the use of artificial neural networks. These networks, specifically transformer-based architectures, allow LLMs to understand the context and relationships between words and phrases, enabling them to generate coherent and contextually appropriate responses.

Finally, natural language processing is at the core of LLMs, as they are designed to understand, generate, and interact with human language. By utilizing NLP techniques, LLMs can perform tasks such as sentiment analysis, text summarization, translation, and question-answering, among others.

Large Language Models are a prime example of the integration of machine learning, deep learning, and natural language processing, showcasing their ability to work together and produce state-of-the-art results in language understanding and generation.

AI in everything

AI, has become an integral part of our daily lives. You might not realize it, but AI is deeply embedded in various aspects of our modern world. Let’s take a closer look at some of the areas where AI plays a crucial role.

First, AI is fundamental in online search engines. When you type a query into a search engine, AI algorithms work behind the scenes to understand your intent and deliver the most relevant results, making it easier to find the information you’re seeking.

In the media, AI is employed to personalize content recommendations, tailoring your viewing or reading experience based on your preferences and past behavior. This technology helps ensure that you’re presented with content that matches your interests.

AI also revolutionizes the field of programming, with tools that can automatically detect bugs, suggest code improvements, and even write entire segments of code, making developers’ work more efficient and less error-prone.

In healthcare, AI is a game-changer, as it can analyze medical images, predict potential health issues, and suggest treatment plans. This technology assists doctors in making more informed decisions and delivering better patient care.

In the world of finance, AI algorithms are employed for fraud detection, risk assessment, and investment management, making financial transactions more secure and efficient.

As a final example, AI is transforming education, providing personalized learning experiences, automating administrative tasks, and even assisting teachers in identifying students who may need extra help.

AI is now an integral part of our lives, impacting numerous areas such as the areas I just explored, as well as in many more. And as AI continues to advance, it will undoubtedly play an even larger role in shaping our future experiences and interactions.

AI in business

AI is revolutionizing the way companies operate, and in this context I will outline three areas where AI is making a difference: personalization, automation, and data-driven decision making.

In regards to the first area, personalization we see how AI today allows businesses to tailor their products and services to individual customers’ needs and preferences. For example, online retailers use AI to recommend products based on your browsing history and past purchases. This level of personalization not only enhances the customer experience but also increases the likelihood of repeat business.

Next, we have automation. AI is streamlining numerous business processes by taking over repetitive and mundane tasks, freeing up employees to focus on more strategic and creative work. From automating customer support with chatbots to managing inventory in real-time, AI-driven automation is increasing efficiency and reducing operational costs.

Finally, data-driven decision making strides in business. AI can analyze vast amounts of data quickly and accurately, providing valuable insights that inform strategic decisions. This capability allows companies to optimize their operations, identify new opportunities, and mitigate risks more effectively than ever before.

As AI technology continues to advance, it will become an even more essential tool for companies seeking to stay competitive and innovative in today’s rapidly changing business landscape.

AI in government

AI has the potential to play an important role in the way governments operate and serve their citizens in several different ways.

For example, AI can enhance public services by streamlining processes, reducing costs, and improving the overall quality of services provided. By utilizing AI-powered tools, governments can efficiently manage resources, automate administrative tasks, and better serve the needs of their citizens in areas such as healthcare, education, and social welfare.

One area where AI makes advances is in the context of smart cities. AI technologies are playing an important role in the development of smart cities, which aim to improve urban living through better management of resources and infrastructure. AI can analyze data from various sources, such as traffic patterns, energy consumption, and environmental conditions, to optimize city planning, transportation, and waste management. This leads to more efficient, sustainable, and livable urban environments.

AI is alsoi increasingly being used in the realm of national security. AI-powered systems can help governments monitor and analyze potential threats, enhance cybersecurity, and support decision-making in crisis situations. By leveraging AI, governments can better protect their citizens and maintain national security in an increasingly complex world.

As you see, AI can play a crucial part in the development of government operations in many different ways, and as AI continues to evolve, its potential to reshape the public sector and improve the lives of citizens will only continue to grow.

AI and the workforce

In thinking about artificial intelligence, many discussions arise on its possible impact on the workforce.

Job displacement is a concern for many, as AI has the potential to automate tasks that were previously performed by humans. In some cases, this can lead to a reduction in the number of employees needed to perform certain jobs. However, it is also important to recognize that technology has always caused job displacement throughout history, and societies have adapted by creating new roles and industries.

We also see an increase in AI-augmented jobs. These are roles where AI and humans work together, with AI assisting or enhancing human abilities. For instance, AI can help doctors analyze medical images more accurately, or assist customer service representatives in handling customer inquiries more efficiently. In these cases, AI empowers workers to be more effective in their roles. In some fields, the speed of adoption of AI is nearly overwhelming, such as in fields such as programming, where AI tools rapidly have become essential parts of work.

Finally, new job opportunities will arise as AI continues to develop. These can include roles in AI research, development, and implementation, as well as jobs that focus on the ethical and societal implications of AI. Additionally, as AI creates new industries and services, more roles will emerge to support these new areas of growth.


The impact on education is becoming increasingly significant. One such area is personalized learning. AI-powered educational platforms can analyze individual students’ learning styles, strengths, and weaknesses to create tailored learning experiences. This personalized approach helps students learn at their own pace and enhances their engagement, leading to improved outcomes and better retention of knowledge.

We also see an emerging adoption of AI in teaching. AI can assist teachers by automating administrative tasks, such as grading assignments and tracking student progress. This frees up valuable time for teachers to focus on more critical aspects of their work, like developing engaging lesson plans and providing one-on-one support to students. Additionally, AI-powered tools can help teachers identify struggling students, allowing for timely interventions and targeted support. At the same time, these practices pose long term risks, as the knowledge needed to learn how to plan, organize and carry out assessment is something that teachers today train. Here, the apparent short term benefits of outsourcing these practices to AI, might also risk long term problems.

There are many more areas of education where AI might play a role, and navigating learning and teaching practices in the age of AI will be important to consider for all in the field.

Research and development

Research and development of AI is exceptionally fast paced today. In labs in both research institutions as well as in businesses, the speed of development is astounding

There are several research areas where work is carried out in a wide range of topics, including machine learning, natural language processing, computer vision, and robotics. Researchers in these areas work on developing algorithms, models, and systems that enable machines to learn, reason, and problem-solve in ways similar to human intelligence.

There are several breakthroughs and milestones in research and development that mark significant moments in the evolution of AI. These achievements, such as the development of deep learning techniques or the success of AI models like AlphaGo, and the current explosion of research and development of Large Language Models, demonstrate the progress and potential of AI technology. These milestones not only serve as benchmarks for future research but also inspire researchers and developers to push the boundaries of AI capabilities further.

When it comes to future directions in AI research and development, the pace continues to be fast, and the ride is sometimes bumpy. As researchers continue to explore new techniques, applications, and ethical considerations, the possibilities for AI will expand, while more complexity will be understood or brought to light. Key areas of focus may include improving AI explainability and transparency, addressing biases in AI systems, and exploring new applications for AI in fields such as healthcare, education, and sustainability.

AI Ethics

AI, continues to advance and integrate into our daily lives, it’s essential to consider the ethical implications of this technology.

Let’s first mention bias and fairness. AI systems are trained on vast amounts of data, and if that data contains biases, the AI may inadvertently perpetuate or even amplify those biases. In the development of AI, it is important to ensure fairness by for example using diverse, representative data and developing methods to detect and mitigate bias in AI models. This will help create AI systems that are more equitable and unbiased in their decision-making.

Futhermore, transparency and explainability are vital to building trust in AI systems. When AI makes a decision, it’s essential for users to understand how and why that decision was made. Developing explainable AI models and ensuring that AI systems are transparent in their operations will enable users to trust and rely on AI technology in a more informed manner.

Lastly, privacy and security are of paramount importance in the age of AI. As AI systems process large amounts of personal and sensitive data, we must ensure that this data is protected and secure. Implementing strong data protection measures and continuously updating AI systems to guard against potential threats is essential in maintaining privacy and security.


AI, becomes increasingly prevalent in our lives, the need for effective regulation to govern its use also grows. In our Swedish context, lets just briefly touch on GDPR and AI. The General Data Protection Regulation, or GDPR, is a European Union law that governs data privacy and protection. While not specifically designed for AI, GDPR has implications for AI systems, as they often process personal data. Ensuring that AI systems comply with GDPR helps protect individuals’ privacy and ensures the responsible use of their data. We have already seen how regulatory authorities are looking into AI and how it relates to GDPR, and we will hear more of this in the coming years.

We also see how AI-specific regulation is emerging as a critical aspect of AI governance. Governments worldwide are recognizing the possible need for tailored policies that address AI’s unique challenges, such as bias, transparency, and accountability. These regulations can help ensure that AI is developed and deployed ethically and responsibly, benefiting both individuals and society as a whole. This regulatory field is still very novel, and new means of actually enabeling regulation whilst at the same time empowering innovation are expored through such practices as regulatory sandboxes. These are envoronments where policy makers, lawyers, entrepreneurs and others meet to engage in cooperative practices that enable for new policy to be developed in close vicinity of the technological development.

Finally, cross-border collaboration is crucial in the realm of AI regulation. AI technology transcends national borders, and its impact is felt globally. To effectively regulate AI, countries must work together, sharing best practices and coordinating efforts to establish international standards and guidelines. We need to see more transnational collaboration in this field, as it will help create a better and more global regulatory framework that ensures the safe and ethical development of AI.


There are of course many risks in regards to AI and its development today.

Let’s consider security threats. As AI systems become more advanced, so do the potential threats they can pose. For example, AI-powered cyberattacks can be more sophisticated and harder to detect, putting businesses, governments, and individuals at risk. It is crucial to invest in robust security measures and stay vigilant to guard against such threats.

Another risk is the possible loss of privacy, that is a relevant concern in the age of AI. AI systems often rely on personal data to function effectively, which can lead to privacy concerns if not managed responsibly. Implementing strong data protection measures and ensuring compliance with privacy regulations, such as GDPR, is essential to protect individuals’ privacy and maintain trust in AI technology.

One final risk to mention in this context is the misuse of AI.  We already see that AI can be used for malicious purposes, such as creating deepfake videos, spreading disinformation, or automating surveillance systems that infringe on personal freedoms. To mitigate these risks, we need to see governments, businesses, and the society at large take action on several levels. This can be everything from regulation, to business ethics or for journalists and watchdogs to call out misuse or bad actors.

Public-Private Partnerships

As artificial intelligence continues to advance, the need for collaboration between public and private sectors has never been more apparent. To start this tipic of, we need to see more collaborative research. By working together, public institutions and private companies can pool their expertise and resources to conduct cutting-edge AI research. This collaboration fosters innovation and accelerates the development of new AI technologies, which can benefit society as a whole.

Co-development of AI solutions is also a powerful way for public and private organizations to address pressing challenges. By combining their unique strengths, such as public sector knowledge of policy and regulation with private sector expertise in technology development, these partnerships can create AI solutions that are both innovative and practical. For example, public-private partnerships can work together on projects like improving urban planning, optimizing transportation systems, or enhancing public health initiatives.

We can also see that sharing of resources and knowledge is crucial to fostering a thriving AI ecosystem. Public and private organizations can benefit from exchanging data, technology, and best practices, helping each other overcome obstacles and harness the full potential of AI. This collaborative approach can also help bridge the gap between research and real-world implementation, ultimately bringing AI’s benefits to a broader audience.

Artificial future outlook

Throughout this presentation, we have explored the numerous applications, possibilities, and challenges associated with AI. We have seen how AI is revolutionizing various sectors, from education and healthcare to business and sustainability, offering improved efficiency, enhanced decision-making, and countless societal benefits. However, we must also recognize and address the risks, such as security threats, privacy concerns, and potential misuse of AI.

To embrace AI responsibly, we must strike a balance between its opportunities and risks. This involves establishing ethical guidelines, regulations, and best practices to ensure that AI is developed and used in a manner that respects human rights, privacy, and security. It is crucial to prioritize transparency, fairness, and accountability in AI systems, ensuring that their benefits are accessible to all.

Moreover, ongoing collaboration and dialogue are vital in shaping the future of AI. This includes fostering public-private partnerships, engaging in cross-border collaborations, and maintaining an open discourse among stakeholders, such as researchers, businesses, governments, and citizens. By working together, we can create a more inclusive, ethical, and sustainable AI landscape.

In conclusion, the future outlook of AI is promising, but it is our collective responsibility to embrace AI technology responsibly. By balancing opportunities and risks and fostering ongoing collaboration and dialogue, we can unlock AI’s full potential while ensuring its positive impact on our world and future generations.

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