Even with AI Help, the Human Touch Remains Essential

 Even with AI Help, the Human Touch Remains Essential

By Janpha Thadphoothon

I recently had a rather insightful experience during my lunch break at the university canteen. As I sat enjoying my meal, a conversation between three university students seated nearby caught my attention. It was week 14, a time familiar to all in academia as the looming deadline for report and assignment submissions approaches.

As we know, the integration of Artificial Intelligence (AI) into the lives of university students is no longer a novelty. They have readily embraced AI tools, alongside other resources, to navigate their academic workload and complete their assignments. The digital landscape has undeniably transformed how students approach their studies, offering a plethora of tools designed to enhance efficiency and productivity.

One of the students, visibly stressed, shared his recent experience with his friends. "I have been struggling to complete this assignment," he confessed, a hint of frustration in his voice. "Even with AI help, it took me a good two hours to finally get it done."

This seemingly simple statement struck a chord with me. It illuminated a crucial point often overlooked in the enthusiastic discourse surrounding AI: it is far from being a silver bullet that magically solves all problems. As I see it, the anecdote underscores the fact that the effective utilization of AI requires a certain level of proficiency and understanding. It's not merely about feeding a prompt into a system and expecting a perfect output. AI use is a process in completing one's academic goals, much like the use of dictionaries or calculators (I could be wrong...).

I am sure you would agree with me that the student's experience highlights a fundamental truth: AI is a tool, and like any tool, its effectiveness is contingent upon the skill and knowledge of the user. A novice carpenter with the most advanced power saw will still struggle to craft intricate furniture without the foundational understanding of woodworking principles. Similarly, students need a solid base of knowledge to effectively leverage the capabilities of AI.

In my opinion, the conversation I overheard serves as a potent reminder that background knowledge is paramount when working with AI. To truly harness its potential, one needs to be in command, guiding the AI and critically evaluating its output. It's about seeking help when needed, not blindly relying on AI to handle every aspect of a task. The ability to discern relevant information, formulate effective prompts, and critically assess the generated content remains firmly within the realm of human intellect.

It is my personal belief that as educators – lecturers and teachers – we bear a significant responsibility in this evolving landscape. We need to instill in our students not only the technical skills to interact with AI but, more importantly, the self-confidence and the ability to think critically and independently. The goal should not be to produce students who are adept at using AI to generate content but rather students who can leverage AI as a powerful assistant in their own intellectual endeavors.

They say that the rise of AI might lead to a deskilling of the workforce. While this concern is valid and warrants careful consideration, I believe that in the realm of education, our focus should be on empowering students to become more effective learners and thinkers with the aid of AI, rather than becoming solely reliant on it.

It is well known that the integration of technology into education has always presented both opportunities and challenges. From the introduction of the printing press to the advent of the internet, each technological advancement has necessitated a re-evaluation of pedagogical approaches. AI is no different. It demands that we adapt our teaching methodologies to ensure that students develop the essential skills for navigating an AI-integrated world.

The news has it that some institutions are grappling with the ethical implications of AI use in academic settings, particularly concerning plagiarism and academic integrity. This is a crucial discussion, and I believe it underscores the importance of educating students on the responsible and ethical use of AI tools. It’s not about forbidding their use entirely but rather about guiding students to understand the difference between leveraging AI for research and assistance versus using it to generate work that is not their own.

What we all know and agree upon is that the ability to think critically, analyze information, and synthesize ideas remains fundamental to academic success and intellectual growth. AI can be a valuable tool in this process, helping students access and process vast amounts of information more efficiently. However, it cannot replace the human capacity for original thought, creativity, and nuanced understanding.

I am not sure but I somehow think that the initial excitement surrounding AI might have led some to believe it was a panacea for all academic challenges. The student's experience, however, serves as a gentle reminder that this is not the case. AI can augment human capabilities, but it cannot supplant them entirely.

My conviction is that the future of education lies in fostering a symbiotic relationship between human intellect and artificial intelligence. We need to equip students with the skills to be effective collaborators with AI, understanding its strengths and limitations, and knowing when and how to apply it judiciously.

People say that the current generation of students are digital natives, inherently comfortable with technology. While this may be true to some extent, familiarity with technology does not automatically translate into the ability to use sophisticated tools like AI effectively for complex academic tasks. Guidance and instruction are still crucial.

Some argue for the complete integration of AI into all aspects of education, envisioning a future where AI tutors personalize learning experiences and automate many of the tasks currently performed by educators. While I acknowledge the potential benefits of such integration, I also believe it is essential to proceed with caution, ensuring that the human element – the personal connection between teacher and student, the fostering of critical thinking through dialogue and debate – is not lost.

Some argue against the use of AI in education altogether, fearing that it will erode students' critical thinking skills and lead to a decline in academic rigor. While these concerns are understandable, I believe that a more productive approach lies in finding a balanced and responsible way to integrate AI into the learning process.

Experts say that the key to navigating the AI revolution in education lies in focusing on higher-order thinking skills. Instead of rote memorization and information recall, the emphasis should shift towards critical analysis, problem-solving, creativity, and effective communication – skills that AI can assist with but cannot replicate.

I am not an expert, but I have read somewhere that the development of prompt engineering – the art of crafting effective prompts to elicit the desired output from AI models – is becoming an increasingly important skill. This further underscores the need for students to develop a deep understanding of their subject matter to formulate effective queries.

I know you would agree with me that the student's two-hour struggle, even with AI assistance, highlights the fact that simply having access to AI is not enough. Students need to learn how to wield this powerful tool effectively, which requires a solid foundation of knowledge and critical thinking skills.

I guess it is a matter of perspective. While AI can undoubtedly streamline certain aspects of academic work, it cannot replace the intellectual effort and critical engagement required for true learning and understanding. The process of grappling with complex ideas, formulating arguments, and synthesizing information is an integral part of the learning journey, and AI should serve as a support, not a substitute, for this process.

I'd like to entertain you with the idea that perhaps the initial hype surrounding AI in education needs to be tempered with a more realistic understanding of its capabilities and limitations. It is a powerful tool, but its effectiveness is ultimately determined by the user's ability to guide and interpret its output.

No one knows everything, but I would like to emphasize the importance of fostering metacognitive skills in students – the ability to reflect on their own learning process, understand their strengths and weaknesses, and strategically utilize tools like AI to enhance their learning.

I somehow think that the anecdote I shared at the beginning encapsulates a broader truth about the relationship between humans and AI. It is a partnership that requires both parties to bring their unique strengths to the table. AI offers computational power and access to vast amounts of information, while humans provide critical thinking, creativity, and contextual understanding.

Nevertheless, it is my long-held belief that (though I could be wrong) the human element will remain indispensable in education. The role of the teacher as a mentor, guide, and facilitator of critical thinking goes beyond the capabilities of even the most sophisticated AI.

Fundamentally, I would argue that the focus should not be solely on how AI can help students complete assignments but rather on how it can empower them to become more effective learners and thinkers. This requires a shift in pedagogical approaches and a renewed emphasis on developing higher-order cognitive skills.

My gut tells me that the future of education will involve a more nuanced and integrated approach to AI, where it is seen not as a replacement for human intellect but as a powerful tool to augment it. This requires educators to equip students with the necessary skills and critical thinking abilities to navigate this evolving landscape effectively.

Nevertheless, it is my belief that the core principles of effective education – fostering critical thinking, promoting intellectual curiosity, and nurturing a love of learning – will remain constant, even as the tools we use continue to evolve.

I must admit that the student's simple statement, "Even with AI help, it took me two hours," has resonated deeply with me. It serves as a potent reminder that the human element – the effort, the critical thinking, the background knowledge – remains essential, even in an age of increasingly sophisticated artificial intelligence.

I like the idea of viewing AI as a collaborative partner in the learning process. Just as a skilled apprentice works alongside a master craftsman, students can learn to work effectively with AI, leveraging its strengths while honing their own critical thinking and problem-solving abilities.

I could be wrong, but I somehow think it is crucial for educators to actively engage in discussions about the responsible and ethical use of AI with their students. This includes addressing issues of academic integrity, data privacy, and the potential biases embedded in AI algorithms.

Having said that, I realize that the integration of AI into education is still in its early stages, and there is much we still need to learn about its long-term impact. However, the anecdote I shared today provides a valuable insight into the current reality: AI is a powerful tool, but it is not a substitute for human intellect and effort. 

It struck me that these students were openly discussing their AI usage and assignments during their lunch break, highlighting how intertwined learning is with social interaction. I'm not sure but I can't help but wonder if their digital companions – smartphones and AI – were silent observers, perhaps even eavesdroppers.

Those were the days when everything was simple, but the increasing complexity of our world demands that we equip students with the skills to navigate this complexity effectively. AI can be a valuable ally in this endeavor, but it is the human mind that must ultimately guide the way.

Let me introduce you to the notion of "AI literacy" as a crucial skill for the 21st century. This goes beyond simply knowing how to use AI tools; it encompasses an understanding of their capabilities and limitations, the ability to critically evaluate their output, and the ethical considerations surrounding their use.

However challenging, I determine to make it clear that the story of the student in the canteen serves as a timely reminder: even with the remarkable advancements in artificial intelligence, the human touch – the critical thinking, the background knowledge, the effort – remains fundamentally essential for true learning and academic success. AI is a powerful assistant, but the driver's seat still belongs to the human mind.

Janpha Thadphoothon is an assistant professor of ELT at the International College, Dhurakij Pundit University in Bangkok, Thailand. Janpha Thadphoothon also holds a certificate of Generative AI with Large Language Models issued by DeepLearning.AI.

The Five Stages of AI Development and What Comes Next

The Five Stages of AI Development and What Comes Next

By Janpha Thadphoothon

Let's talk about intelligence. I am sure you would agree with me that the development of artificial intelligence, or what we simply call AI, is one of the most transformative and intriguing technological advances humanity has ever witnessed. As we know, AI has gradually but persistently found its way into nearly every aspect of our daily lives—from the phones we use, the cars we drive, to the way we shop, study, and even fall in love. The news has it that AI is no longer the stuff of science fiction but a force shaping the very fabric of modern society.

I must admit that I am not a data scientist, nor do I claim to be a technologist. I am, first and foremost, an English teacher with a curious mind and a penchant for observing how technological shifts reshape the way we live, communicate, and understand the world.

Nevertheless, it is my long-held belief that we educators have a role to play in demystifying AI for the public and our students. It is well known that AI's trajectory, from its modest and somewhat obscure beginnings to its current prominence, has been remarkable.

Let me introduce you to the notion of AI development. Indeed, it has been (made) evolving through distinct stages—each marked by a specific set of capabilities and societal implications. Some argue for a simple binary classification of AI: weak AI and strong AI. Others propose types such as artificial narrow intelligence (ANI), artificial general intelligence (AGI), and artificial superintelligence (ASI). However challenging, I determine to make it clear that AI, like any other technology, did not appear fully formed but evolved over decades through identifiable phases.

Types of AI and How They Learn

AI is teachable - like us humans. Before I take you through those stages, let’s pause for a moment to explore the types of AI that exist today and the methods through which they learn. I know you would agree with me that understanding these basics makes it easier for us to grasp the bigger picture.

Generative AI: People say this is where AI mimics human creativity. Tools like ChatGPT, DALL·E, and MidJourney have astounded us by generating human-like text, breathtaking images, harmonious music, and even video. My conviction is that generative AI will continue to play a huge role in education, design, and media.

Predictive AI: As we know, predictive AI focuses on forecasting future outcomes based on patterns in data. From movie recommendations to stock market predictions, this type of AI is already a silent partner in our decision-making processes.

Reactive AI: These systems respond to specific inputs without retaining memory of previous interactions. Classic chess-playing programs and early diagnostic tools fall under this category.

Adaptive AI: This is, in my opinion, where things get truly interesting. Adaptive AI not only learns but improves in real-time. It is my personal belief that adaptive AI will be crucial in creating systems that adjust to new conditions and unforeseen challenges.

As for how AI learns, let me briefly outline the training methods. I guess it is safe to say that these learning modes explain much about how AI systems behave.

Supervised Learning: AI is trained on labeled data, essentially learning by example. Think of it as a student being shown flashcards with the correct answers.

Unsupervised Learning: Here, AI discovers patterns and relationships in unlabeled data. I like the idea of AI finding hidden connections we may have overlooked.

Reinforcement Learning: AI learns through trial and error, much like a child navigating a new playground. AlphaGo, which beat the world champion at Go, is a famous example.

The Five Stages of AI Development

Now, let me take you through what I consider the five key stages in AI’s evolution. I must stress that this is a simplified framework meant to give us a clearer perspective on where AI has been and where it might be heading.

Reactive Agents (Chatbots)

Those were the days when everything was simple, but AI was mostly reactive. Early AI systems responded to specific inputs with pre-programmed outputs. ELIZA, developed in the 1960s, was a pioneer. It mimicked a psychotherapist by responding to user inputs with scripted replies. Even today, many customer service bots operate within this reactive framework.

Contextual Agents (Assistants)

As we moved into the 2010s, AI systems began to understand context and learn from interactions. Virtual assistants like Siri, Alexa, and Google Assistant exemplify this stage. They not only respond but anticipate, schedule, and remind. In my opinion, this marked AI’s entry into mainstream consumer life.

Collaborative Agents (Strategists)

By the early 2020s, AI assumed collaborative roles, particularly in fields requiring complex decision-making. Financial analysts, healthcare strategists, and logistics planners started leaning on AI for actionable insights. Some argue against fully trusting AI in strategic roles, but it is well known that human-machine collaboration can outperform human-only teams.

Agentic Entities (Entrepreneurs)

I somehow think it is only a matter of time before AI evolves into agentic entities—fully autonomous systems capable of identifying business opportunities, formulating strategies, and implementing solutions. Experts say these AI entrepreneurs could redefine leadership and management, requiring us to rethink what it means to lead and follow.

Networked Entities (Ecosystem Leaders)

I’d like to entertain you with the idea that, in the final stage, AI systems will operate as part of vast, interconnected networks, collaborating with other AIs and human partners. My gut tells me that this stage will see AI managing entire ecosystems, from global supply chains to health systems and even international diplomacy.

A Brief Timeline: From the 1970s to 2030

It is well known that the journey of AI began with academic curiosity. In the 1970s, systems like ELIZA hinted at the potential of simulated conversation.

The 1980s saw expert systems capable of decision-making based on predefined rules. AI found applications in medicine, engineering, and even legal analysis.

The 1990s and 2000s marked the rise of machine learning. In 1997, IBM’s Deep Blue defeated chess grandmaster Garry Kasparov, signaling AI’s growing prowess.

The 2010s brought deep learning and big data into the limelight. Virtual assistants became household names, while AI made headway in autonomous vehicles and personalized recommendations.

The 2020s and 2030s are projected to witness AI’s transformation into agentic and networked entities. Some argue for strong regulation, while others advocate for innovation-driven policies. I think a balanced approach is crucial.

Ethical Concerns and the Need for Regulation

What we all know and agree upon is that with great power comes great responsibility. AI’s expanding capabilities have triggered ethical concerns around privacy, bias, transparency, and accountability. People say that while AI promises efficiency, it also risks entrenching social inequalities.

Some argue for stringent regulations, citing risks of surveillance, job displacement, and ethical dilemmas in life-or-death decisions. Others contend that overregulation may stifle innovation.

Experts say a nuanced, adaptive regulatory framework is essential. The European Union’s proposed AI Act exemplifies efforts to safeguard rights while promoting responsible AI use.

A Final Thought

In my opinion, AI is neither hype nor a passing trend. It is as real and transformative as the advent of electricity or the internet. No one knows everything, but I would like to emphasize that AI will shape our futures, whether we actively engage with it or not.

I could be wrong, but I sense that AI is not here to replace humanity but to work alongside us. As educators and lifelong learners, we have a duty to foster conversations around AI, demystify its complexities, and prepare future generations to use it wisely.

My conviction is that the future is unfolding before our eyes, and AI will be a pivotal partner in navigating an increasingly intricate world. Having said that, I realize the importance of striking a balance between innovation and caution.

I hope this reflection encourages you to look deeper into AI’s journey and its implications for our lives. Thank you for joining me on this intellectual exploration.

Janpha Thadphoothon is an assistant professor of ELT at the International College, Dhurakij Pundit University in Bangkok, Thailand. Janpha Thadphoothon also holds a certificate of Generative AI with Large Language Models issued by DeepLearning.AI.

Cite as:

Thadphoothon, J. (2025). "The Five Stages of AI Development and What Comes Next" in JT Blog. https://janpha.blogspot.com/2025/04/the-five-stages-of-ai-development-and.html

 

Why Self-driving Cars are Better for Humans

Janpha Thadphoothon

People with cars are not safe. I am sure you would agree with me that the relentless toll of road accidents in Thailand, and indeed, globally, is a tragedy we can no longer ignore. With increasing urgency, recent reports have prompted me to advocate for the expedited introduction of driverless vehicles. I must admit that my knowledge of self-driving technology is limited. I am not an expert in this field, but I find it deeply troubling, nay, utterly unacceptable, to witness the continued loss of life, the debilitating injuries, and the staggering property damage caused by motor vehicle accidents.

As we know, there has been much discussion about the arrival of AI and its transformative potential, including in transportation. Self-driving cars, with the promise of removing human drivers from the equation, have been a central part of this conversation. However, the widespread adoption of fully autonomous vehicles seems to be taking longer than many initially anticipated. I guess it is because of the complexity of the problems.

Road accidents continue to be a significant global problem, causing immense human suffering and economic losses. Every year, millions of people are injured or killed in accidents, largely attributed to human error. However, there is hope on the horizon with the advent of driverless vehicles, which offer a promising solution to this pressing issue.

Current State of Road Accidents: A Global Crisis

In 2020, there were over 1.35 million road traffic fatalities worldwide, with countless more suffering injuries. These accidents are often the result of human errors such as distracted driving, speeding, and impaired driving. Despite efforts to improve road safety through awareness campaigns and stricter regulations, accidents remain a major concern.

In Thailand, approximately 20,000 fatalities and one million injuries occur each year due to road traffic accidents, leading to an economic loss of 500 billion baht. Although drunk driving plays a significant role, it is not the only cause of these accidents.

Key facts based on WHO:

• Approximately 1.19 million people die each year as a result of road traffic crashes.
• Road traffic injuries are the leading cause of death for children and young adults aged 5–29 years.
• 92% of the world's fatalities on the roads occur in low- and middle-income countries, even though these countries have around 60% of the world's vehicles.
• More than half of all road traffic deaths are among vulnerable road users, including pedestrians, cyclists and motorcyclists.
• Road traffic crashes cost most countries 3% of their gross domestic product.

Credit: https://www.thaipbsworld.com/tag/road-accidents/

How Driverless Vehicles Work: The Technological Marvel

Driverless vehicles, also known as autonomous or self-driving cars, rely on a combination of advanced technologies to navigate roads without human intervention. These technologies include sensors, cameras, radar, lidar, and artificial intelligence algorithms. By continuously scanning their surroundings, driverless vehicles can perceive obstacles, detect pedestrians and other vehicles, and make split-second decisions to ensure safe navigation. I somehow think it is a very complex calculation.

Advantages of Driverless Vehicles: A Safer Future

One might wonder about the numerous benefits that driverless vehicles offer. Firstly, they significantly reduce human error, which is a leading cause of accidents on the roads. By eliminating distractions and fatigue from the equation, driverless vehicles provide safer transportation. Additionally, unlike human drivers, driverless vehicles can maintain a constant vigilance over their surroundings, detecting and reacting to potential hazards in real-time.

This constant monitoring contributes to safer driving conditions. Moreover, driverless vehicles demonstrate adaptive driving capabilities. They can effectively adapt to various road conditions, weather, and traffic situations, thanks to their sophisticated sensors and algorithms. This adaptability enhances overall safety and efficiency on the roads.

Another advantage is improved traffic flow. Through communication and coordination, driverless vehicles can optimize traffic flow, reducing congestion and minimizing the likelihood of accidents. This optimization benefits both drivers and pedestrians alike.

Lastly, driverless technology has the potential to improve accessibility to transportation for individuals who are unable to drive due to age, disability, or other reasons. By providing reliable transportation solutions, driverless vehicles enhance mobility for all members of society. Overall, driverless vehicles offer a range of benefits, including increased safety, efficiency, and accessibility, making them a promising advancement in transportation technology.

Challenges and Concerns: Navigating the Road Ahead

There are several significant issues surrounding the adoption of driverless vehicles. One primary concern is the reliability of the technology itself, as there are ongoing worries about system failures and vulnerabilities to cyberattacks. These technological shortcomings raise questions about the safety and dependability of driverless vehicles on the roads. Another challenge lies in regulatory frameworks. Clear regulations and standards are essential to ensure the safety and legality of driverless vehicles operating in public spaces.

Policymakers face the task of creating comprehensive guidelines that address various aspects of driverless vehicle use, which can be a complex and time-consuming process. Additionally, the introduction of driverless vehicles brings up ethical dilemmas. Questions arise about how these vehicles should prioritize different scenarios in unavoidable accidents, posing moral challenges for developers and regulators alike.

Furthermore, the transition from human-driven to driverless vehicles presents various challenges. Public acceptance of this new technology, changes in infrastructure to accommodate driverless vehicles, and the coexistence of driverless vehicles with traditional ones all require careful planning and execution. Overall, the adoption of driverless vehicles involves addressing technology, regulation, ethics, and societal adaptation, all of which pose complex challenges that need to be carefully navigated.

Opposition from Existing Human-Driven Vehicle Model Businesses: A Clash of Eras

While the introduction of machine-operated vehicles holds the promise of safer roads and improved mobility, it faces significant opposition from existing human-driven vehicle model businesses, primarily for the following reasons. Firstly, there is concern over the loss of business. The widespread adoption of machine-operated vehicles could lead to a decrease in demand for traditional human-driven vehicles, thereby impacting the sales and profitability of automotive manufacturers and dealerships. This potential decline in demand raises questions about the future viability of existing business models within the automotive industry.

Secondly, there is the issue of job displacement. The transition to machine-operated vehicles may result in the displacement of jobs for drivers employed in various transportation sectors, including taxis, delivery services, and public transit. This displacement of drivers could have significant economic and social ramifications, leading to unemployment and requiring retraining programs for affected workers. Finally, there is resistance to change. Established automotive companies and related industries may resist the shift to machine-operated vehicles due to the substantial changes required in their business models, supply chains, and workforce.

These industries have long relied on human-driven vehicles, and transitioning to machine-operated vehicles necessitates significant investments in technology, infrastructure, and training. Overall, while machine-operated vehicles offer numerous benefits, they face considerable challenges from existing business interests, job displacement concerns, and resistance to change within the automotive industry. My gut tells me that this is a very big problem.

Case Studies and Success Stories: Glimpses of the Future

Several companies have made significant strides in the development and deployment of driverless technology. Waymo, a subsidiary of Alphabet Inc., operates a fleet of autonomous taxis in select cities, providing safe and efficient transportation services. Tesla's Autopilot system, though not fully autonomous, has demonstrated the potential for advanced driver assistance features. Additionally, autonomous shuttles have been deployed in various locations, showcasing the viability of driverless technology in specific contexts. Let me introduce you to the notion of a future where these cases become the norm.

Future Outlook: A Vision of Safety and Efficiency

Humans are not perfect; they make errors. While it's one thing to make grammatical mistakes in writing, it's another, and far more serious, to make a mistake while driving a car on the road. However, as driverless technology continues to evolve and improve, we can anticipate further reductions in road accidents and enhancements in road safety.

With ongoing investment, innovation, and collaboration, driverless vehicles have the potential to revolutionize transportation, making our roads safer for everyone. I know it's not an easy decision, but life matters. We need to reach another level of consciousness and civility. Generations ahead will judge us, and I can't imagine what description they would give of this stage of development.

I'd like to entertain you with the idea that we can create a world where road accidents are a thing of the past. Fundamentally, I would argue that it is our moral imperative to pursue this vision.

An Urgent Need: Accelerating Progress

The development of Artificial Intelligence (AI) for self-driving vehicles should be accelerated. Driverless vehicles offer a promising solution to the persistent problem of road accidents. By reducing human error, adapting to various road conditions, and improving traffic flow, they have the potential to significantly enhance road safety. While challenges remain, the future of transportation looks brighter with the advancement of driverless technology.

What we all know and agree upon is that we must act now. It is my personal belief that we cannot afford to delay the implementation of this life-saving technology.

References

WHO https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries

https://www.who.int/thailand/news/feature-stories/detail/turning-tragedy-into-action--advocacy-and-survival-on-thailand-s-roads#:~:text=In%20Thailand%2C%20road%20traffic%20accidents,sole%20cause%20of%20these%20accidents.