3D printing or additive manufacturing is the construction of a three-dimensional object from a CAD model or a digital 3D model.^[1] It can be done in a variety of processes in which material is deposited, joined or solidified under computer control,^[2] with material being added together (such as plastics, liquids or powder grains being fused), typically layer by layer.

In the 1980s, 3D printing techniques were considered suitable only for the production of functional or aesthetic prototypes, and a more appropriate term for it at the time was rapid prototyping.^[3] As of 2019^[update], the precision, repeatability, and material range of 3D printing have increased to the point that some 3D printing processes are considered viable as an industrial-production technology, whereby the term additive manufacturing can be used synonymously with 3D printing.^[4] One of the key advantages of 3D printing^[5] is the ability to produce very complex shapes or geometries that would be otherwise impossible to construct by hand, including hollow parts or parts with internal truss structures to reduce weight. Fused deposition modeling (FDM), which uses a continuous filament of a thermoplastic material, is the most common 3D printing process in use as of 2020^[update].^[6]

Augmented reality (AR) is an interactive experience that combines the real world and computer-generated content. The content can span multiple sensory modalities, including visual, auditory, haptic, somatosensory and olfactory.^[1] AR can be defined as a system that incorporates three basic features: a combination of real and virtual worlds, real-time interaction, and accurate 3D registration of virtual and real objects.^[2] The overlaid sensory information can be constructive (i.e. additive to the natural environment), or destructive (i.e. masking of the natural environment).^[3] This experience is seamlessly interwoven with the physical world such that it is perceived as an immersive aspect of the real environment.^[3] In this way, augmented reality alters one's ongoing perception of a real-world environment, whereas virtual reality completely replaces the user's real-world environment with a simulated one.^[4][5]

Augmented reality is largely synonymous with mixed reality. There is also overlap in terminology with extended reality and computer-mediated reality.

Algorithmic bias describes systematic and repeatable errors in a computer system that create "unfair" outcomes, such as "privileging" one category over another in ways different from the intended function of the algorithm.

Bias can emerge from many factors, including but not limited to the design of the algorithm or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. For example, algorithmic bias has been observed in search engine results and social media platforms. This bias can have impacts ranging from inadvertent privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. The study of algorithmic bias is most concerned with algorithms that reflect "systematic and unfair" discrimination. This bias has only recently been addressed in legal frameworks, such as the European Union's General Data Protection Regulation (2018) and the proposed Artificial Intelligence Act (2021).

Generative design is an iterative design process that involves a program that will generate a certain number of outputs that meet certain constraints, and a designer that will fine tune the feasible region by selecting specific output or changing input values, ranges and distribution. The designer doesn't need to be a human, it can be a test program in a testing environment or an artificial intelligence, for example a generative adversarial network. The designer learns to refine the program (usually involving algorithms) with each iteration as their design goals become better defined over time.^[1]

The output could be images, sounds, architectural models, animation, and much more. It is therefore a fast method of exploring design possibilities that is used in various design fields such as art, architecture, communication design, and product design.^[2]

The process combined with the power of digital computers that can explore a very large number of possible permutations of a solution enables designers to generate and test brand new options, beyond what a human alone could accomplish, to arrive at a most effective and optimized design. It mimics nature’s evolutionary approach to design through genetic variation and selection.^{[citation needed]}