Innovation through partnership: Machines and Humans

Recently, there has been the shift by several organisations, nations and even people to ditch humans and chase the productivity that comes with just the use of machines. This happens sometimes because of the need to reduce the time to market of products, the need to make quick profit, the need to increase efficiency (sometimes at the expense of quality) and the faulty thought that machines are better than humans at everything.

With machines producing faster results and performing (functioning) all day long, corporations sometimes feel the need to shift the focus from the need for humans, to what can be achieved with full machine use. Some of these shift can be seen when organisations replace an entire customer support team with chatbots or when human resource personnels are replaced with hiring algorithms or softwares. This shift not only completely eradicates human involvement when making hiring decisions, but also silently affects organisational culture - sending a “silent” message that machines are more valued than humans and also that empathy and ethical judgement does not matter.

The efficiency and speed that come with production and innovation with machines can sometimes also be dangerous and a better approach for corporations would be to understand that humans are extremely needed to “contextualise” as well as “question” both the input and the output of machines. For example, in software development, as much as generative AI tools can “read” and “learn” from their environment, software developers who write code should understand that for complex systems, the exclusive use of generative AI  to code without AI understanding the context for which the code is needed or without understanding the business case can lead to the production of systems that function but do not function as intended.

The difference in the way humans and machines function makes it essential for corporations to think partnership and not replacement when thinking of humans and machines as regards to work. Despite the fact that humans might not be as efficient  or be able to scale like machines, they still contribute immensely to the success of a product. Humans understand business contexts, can question machine output, can reason ethically and usually have a more holistic view factoring in not just efficiency but also thinking about the market for a product, the users, the impact of a product on the society and lots more.

Corporations that intend to have the best of both worlds should train their employees to collaborate with machines instead of competing with them, innovation should be approached with ethical values instead of just performance or profit, there should be a proper review of the output of machines by humans and human input should be prioritised when it is sensed that machine outputs are unethical or dangerous.

Going the route of partnering with machines instead of replacing humans with machines will further create a partnership that works with machines spotting trends while humans frame them.