Generative AI and the Future of Work

Since the introduction of generative Artificial Intelligence (AI) I've been receiving invitations to take part in conversations on how this new technology will change the future of work. One such invite was very recently, from the University of Cape Town Summer School for a slightly different but similar topic. In the end, due to unforeseen circumstances I couldn't attend, so I thought I'd write an adapted version of this talk here. I also submitted this talk to a conference which shall remain unnamed, this conference rejected this talk :)

Generative AI is a type of AI that lets you create new content and ideas. These can be conversations, stories, images, videos, and music. Similar to all AI, generative AI is powered by Machine Learning (ML) models. The difference between other AI and generative AI is that generative AI is powered by very large models that are pre-trained on large amounts of data known as foundation models (FMs) and these form the basis for generative AI.

Background

With traditional forms of machine learning we can take simple inputs, for example, a numeric value, and map them to simple outputs, like predicted values. I won't pretend to know how machine learning algorithms work but an example of this scenario could be simple input values of 1, 4, 5, 8, and 10 and paired with their corresponding outputs of 7, 13, 15, 21, and 25. The machine learning algorithm then determines the best way to represent the relationship between the input and output. So rather than have to individually program a response for an input of say 1, the model can compute the correct response based on input/response pairs that it has learned.

With deep learning, we take complicated inputs, like videos or images, and map them to relatively simple outputs, like identifying an object in an image. For example, Is there a staircase in this image, Yes or No.

And now, with generative AI, we can use massive amounts of complex data to capture and present knowledge in advanced ways – mapping complicated inputs to complicated outputs, like extracting a summary and rich insights from customer conversations.

Generative AI and Tech Careers

Do you remember when chatbots first became a thing?

Chatbots are just one of the ways in which artificial intelligence has played a pivotal role in augmenting and transforming many aspects of our world. A chatbot is a?software?application or web interface that aims to mimic human?conversation?through text or voice interactions.?Modern chatbots are typically?online?and use AI systems that are capable of maintaining a conversation with a user in?natural language?and simulating the way a human would behave as a conversational partner. Such technologies often use aspects of deep learning?and?natural language processing (NLP), but more simplistic chatbots have been around for decades.

As tech professionals, we have a front-row seat to the rapid advancements in AI, we always have. Generative AI is another prime example of how artificial intelligence continues to augment and transform many aspects of our world.

Earlier in this article I talked about the different types of content that you can create using generative AI (text, images, music, stories, videos). With this ability to create new content and perform many tasks that were traditionally reserved for humans, the rapid rise and integration into everyday life of generative AI has been awe-inspiring, and it will continue to bring change and transform jobs and functions across industries.

It's not shocking then that the prospect of generative AI-driven capabilities and efficiencies has raised concerns about job displacement, with predictions of significant workforce disruption.

A report by Goldman Sachs talks about the fact that generative AI introduces rapid acceleration in task automation which is good news for cost savings and productivity.

Its potential ability to generate content that is indistinguishable from human-created output and to break down communication barriers between humans and machines reflects a major advancement, but this potentially has large macroeconomic effects with significant disruptions to the labor market.

The report further goes on to state that based on studies done on occupational tasks in both the US and Europe, roughly two-thirds of current jobs are exposed to some degree of AI automation, and that generative AI could substitute up to one-fourth of current work. Taking these estimates globally suggests that generative AI could expose the equivalent of 300 million full-time jobs to automation.

Job Automation Over the Years

What if I told you that throughout history humans have always been dependent on technology to reimagine how they do their work? Of course, the technology of each era had its own shape and size. People always used the technology they had available to help make their lives easier, and at the same time try to perfect it and bring it to the next level, most times moving from a manual approach, to an automated approach on how they do work.

So this is how the concept of industrial revolution began. We are in the?fourth industrial revolution.?We are applying (or combining) information and communication technologies to how we do things. The technical enablers of the fourth industrial revolution include the internet of things, big data, robots and cobots, 5G Network, cloud and edge computing, and AI/ML.

Future-Proof Your Tech Career with generative AI

Looking at all that we’ve already discussed, we know that work is changing, so what can we do about it?

As generative AI continues to advance, it's inevitable that certain job roles will undergo transformation.

Rather than resisting it, a better approach is to embrace the technology and explore how it can enhance, expedite and support the work that we do today.

In a recent?research?by Stack Overflow, 70% of more than 67,000 professional developers surveyed were already using or planning to use AI tools.

Integrating AI into tech workflows is complex, and it requires careful evaluation of the potential risks and benefits.

Generative AI will change software development by automating routine tasks, enabling rapid prototyping and customizing solutions.

Software developers can use AI for code suggestions and bug detection—even generating code segments to reduce development time.

Good news if you currently are not a software developer but looking to transition into this role is that the line between “coder” and “non-coder” might even blur over time, because AI can assist in translating natural language queries into code.

Familiarity with generative AI is emerging as a valuable skill for the software developer, engineering and data science, to name a few.

This includes both conceptual understanding of how the technology works as well as hands-on experience with tools such as Amazon CodeWhisperer.

Cloud roles have much to gain from the rise of generative AI. With generative AI, cloud practitioners can streamline their workloads by automating basic infrastructure coding, help realize cloud cost savings by optimizing infrastructure for attributes such as cost and speed, and aid cloud security by identifying data anomalies. The benefits of generative AI for cloud practitioners are endless. - Aaron Skonnard,?Pluralsight

Conclusion

The rise of generative AI is introducing both challenges and opportunities for tech professionals, but it'll be crucial to approach this transformation with adaptability and continuous learning. Generative AI has the potential to reshape the nature of work for a number of jobs, but it also presents exciting opportunities for new roles that may not yet exist.

Human-machine collaboration will play a crucial role in maximizing the benefits of generative AI, as humans possess unique qualities like creativity and emotional intelligence that cannot be replaced by a machine. By embracing this partnership between humans and machines, we can shape a future where technology complements human skills and fosters innovation.

We need to maintain a balanced perspective, understanding that the impact of generative AI on the job landscape will be significant but that humans remain an indispensable part of the equation.

**All photos generated using Stable Diffusion Foundation Model on Amazon Bedrock

Resources

1. How does machine learning work?
2. The Potentially Large Effects of Artificial Intelligence on Economic Growth (Briggs/Kodnani)
3. Stack Overflow Research
4. Generative AI on AWS