The growth of Generative AI and what it means for our jobs


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The emergence of Generative AI and its implications for our jobs As the creators and users of technology, we have long thought that there are certain tasks that machines and software cannot perform. But the advent of Generative Artificial Intelligence (GAI) has made us reconsider this belief and its potential consequences for the boundaries of what machines and software can do. In simple terms, Generative AI is software that can create unique content from existing information. If GAI is widely adopted, it could have a huge impact on society and the economy, as it could reduce or even eliminate the human advantage in creativity. So, what is GAI and what does it mean for our future? 

What is GAI and why is it important? 

Generative AI is a form of Artificial Intelligence (AI) that enables machines to generate new content such as text and images from existing information. A popular example is OpenAI's ChatGPT-3, which can respond to user prompts with text. What makes this software special is how human-like it is in interaction and the extended functionalities it offers. Before 2015, Generative AI was limited to small-scale models, primarily used for text translation. But in 2015, Google Research released a paper titled "Attention is All You Need" which introduced a new type of Machine Learning algorithm, called a "transformer", that increased the realism and detail of Generative AI's creations. This also reduced the amount of data needed to train the software. 

The impact of Generative AI on knowledge workers 

Generative AI can be beneficial for knowledge workers, as it can automate repetitive tasks, reduce the need for technical knowledge, and generate insights. In some cases, such as art, the quality of content created by Generative AI is equal to or better than that of human workers. Generative AI will also create a market for skills in its use and manipulation. However, the impact of Generative AI is not evenly distributed across all sectors. 

Impact of GAI on software developers 

GAI cannot yet produce programs as complex or large as those of the best human programmers. However, there has been significant progress, as seen in the unexpected performance of the coding software AlphaCode in a recent coding competition. The software was able to create algorithms on its own, which is a major milestone for GAI. Nonetheless, the problems solved were fairly simple and required no complex design. Additionally, the cost of constructing and training the model is high, making it cost-ineffective for broad-scale applications. 

Impact on graphic designers and artists 

Generative AI can now produce a variety of high-quality designs, as seen in software such as Midjourney and DALL-E 2. Graphic designers at large companies are already using it to generate simple designs. While some of the current skills may not be necessary for the future, new skills such as prompting and training AI systems will become more valuable. Copyright concerns may also limit its disruption. 

Impact on content writers 

Generative AI has had a limited impact on content writers, as it has poor quality in the absence of substantial pre-existing content, and it can only work well for simple topics. Copyright concerns and opposition from search engines like Google also play a role. 

Other Impacts 

Generative AI is also used in fields such as drug discovery, film dubbing, and video augmentation, but usually in conjunction with human workers.

 At a personal level: 

a. Acquire skills not easily replicated, such as software engineering. 

b. Develop proficiency in skills related to Generative AI, such as prompting. 

c. Utilize it to increase your efficiency, such as using it to generate basic code snippets. 

d. Keep up to date with the most recent advancements in Generative AI. 

At a bigger level: 

Historically, a strong argument can be made for the idea that technological innovation does not eliminate jobs as much as replace them, a trend likely to continue in the future. Therefore, we must mainly prepare for the replacement, and not the eradication of jobs, with some steps for mitigation being: 

a. Compensation for those affected negatively. 

b. Mitigation of other causes of unemployment, such as a lack of education. 

c. Raising public awareness about the effect of Generative AI. 


Given that Generative AI is still in its infancy, we can not accurately predict its impact. Nevertheless, armed with adequate knowledge of history and an understanding of Generative AI, we can prepare for its impact and possibly prevent some of the negative consequences arising from it.

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