Trust me I am an engineer
“Trust me I am an engineer” is statement that is widespread (not only on the internet) and used in all kinds of engineering environments. The phrase meaning that someone is inexperienced or lacking in a skill and yet is pretending to know what they are doing. Do you trust the engineer? In this article, I look at what it means to trust you have in using a product. The design, production process, end-result and all the claims around it, has a trust level. Sometimes we don’t even realize how much trust we place in (using) a product.
What can you trust nowadays? Generative AI can take care of publications and images. Let me start with stating that I am writing this article and it is not generated by any form of AI. Trust me, I am the engineer writing this.
Do you trust the data around you?
There is so much data collected of us as persons, of what we use, where wo go or what we purchase. Algorithms go through your data and create the next advertisement you want to see. Data can be misused in many ways. It can also be manipulated in many ways. It may be difficult for us to trust data and its creations. Working with your own data and your own algorithms can create a safe zone[1]. Trust in you as an engineer.
Do you trust the autonomous operating machines around you?
Autonomous guided vehicles (AGV’s) are commercially available in big and small sizes. They can take care of gathering tiny products in a warehouse for one order. They are also used to move your luggage on airports or building a car. Autonomous robotic arms are what is making dark factories. Dark factories or lights out manufacturing is the methodology of fully automating the production of goods at factories and other industrial facilities, such as to require no human presence on-site. In real life the lights will not be out during production because we want to supervise the running factory or because some light is needed to scan and recognize parts or actions during the manufacturing process. In the case of a “lights-on” dark factory we do not trust the autonomous machines. Laying trust in autonomous machines requires a lot of trust in the product engineering process. Tests done during the entire process helps to build trust. Modelling the first steps while defining the product already helps building trust in the design. Testing of prototypes gives the R&D department trust that an idea might work. Testing during the development process on all possible test levels, builds trust for the end customer. Usage of the product and experience in updating and maintain the product builds trust for the vending organization as well as the end user. This goes for all products: consumer products, whole production facilities, AGV’s, etc.
Do you trust the environmental impact of a product?
Many products have sustainability claims. You must trust the claim to make the choice for a (possibly more expensive) sustainable version of a product. A sustainability statement needs to be backed up with information that is trustworthy enough for it to be real. Not only the materials used in a product effect its sustainability claim. Sustainability is a broad term and can cover up to all the 17 sustainability goals defined by the United Nations. Not only can the use of one material over the other claim the end-product to have reduced water spillage by an X percentage, but the entire production process might also contribute to it. Even the transportation used from raw material to end customer can have an impact on one or more of the 17 sustainability goals. Trusting the sustainability claim is no small feat. Rules and regulations can help, standardized reporting help to fact check claims, but it remains a complicated matter.
[1] Be aware that this statement only holds when you are creating everything by yourself. If you add libraries of created algorithms or download (even though it might be verified) datasets, the trust in ‘your’ data is already compromised.
