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Blade Runner 2049 misses mark on artificial intelligence: U of T experts

Picture of Joi from Blade Runner 20149
In Blade Runner 2049, a holographic artificial intelligence character, Joi, is marketed as a personal companion to the protagonist, K (handout photo)

The portrayal of artificial intelligence in Blade Runner 2049 takes on a nuance absent in the original film. In addition to the advanced intelligence of the replicants 鈥 human-seeming biological machines 鈥 there is also the holographic character Joi, a logical extension of today鈥檚 digital assistants such as , Microsoft鈥檚 or Amazon鈥檚 .

Aside from these two depictions, AI is largely relegated to the background. It鈥檚 performing simple tasks such as running machines, and autonomously piloting spinners (Blade Runner鈥檚 flying cars). It鈥檚 also dynamically altering the environments that people inhabit, causing light to move with them as they walk through beautiful and brutal constructed spaces.

In all of these forms, the film makes a key distinction between human and artificial intelligence: Only people are capable of creativity 鈥 AI is mechanical.

As researchers interested in digital automation and expertise, we can say that Blade Runner 2049鈥檚 depiction of AI as mundane belies today鈥檚 reality and the history of the field.

Recent examples have shown computers have started to become active participants in creative work such as the field of design, collaborating with humans to shape the objects and experiences that fill our daily lives. Moreover, there is also a long history around computation and creativity that needs to be addressed.

In Blade Runner 2049, actor Ryan Gosling plays police officer K who is accompanied by a holographic artificial intelligence character, Joi, played by Ana de Armas (handout photo)

Generative design

The newly emerging field known as 鈥済enerative design鈥 seeks to incorporate the computer more actively into the design process. In these kinds of computer applications, the designer uploads a 鈥渟eed geometry鈥 鈥 akin to a reference drawing an animator might use 鈥 and then sets a series of requirements ranging from the aesthetic to the functional.

The software then searches through a series of designs based on the seed geometry and surfaces those that meet the requirements. The designer can select one of these 鈥渟olutions鈥 for production or to function as the next seed geometry and the process begins again.

The is a recent example of a successful use of generative design that has garnered a great deal of attention. Created in the summer of 2016 by Autodesk researchers Brittany Presten and Arthur Harsuvanakit, the chair was a part of a project examining how to best incorporate generative design tools into traditional computer-aided design (CAD) software.

Generative design uses computation to envision creations in thousands of ways before a person chooses the best one (photo by Autodesk)

A chair was selected for this project, according to Harsuvanakit, because of the surprising complexity of the object. A 鈥済ood鈥 chair not only has to be aesthetically pleasing, but it also needs to be comfortable and support body weight. There is also the issue of 鈥減roduceability鈥 鈥 regardless of how well a solution meets the other requirements, that would mean little if it was not feasible to actually fabricate the chair.

The requirements Presten and Harsuvanakit ultimately settled upon were that the chair was to be produced using wood and a CNC router 鈥 a computer-controlled cutting machine. Functionally, the chair would need to bear a weight of up to 300 pounds and the seat would be 18 inches off the ground.

Aesthetically, Dutch mid-century modern was selected for the chair鈥檚 style, and a seed geometry was created for the chair that paid homage to several chairs from this school of design. The name of the chair itself is a reference to 鈥檚 design icon, Elbow Chair.

The Elbo chair was created using generative design, in which computers co-create with humans 

The final results are striking. With its seemingly strange blend of Danish and almost organic influences 鈥 apt considering that generative design is often likened to the evolutionary processes 鈥 the Elbo chair also uses 18 per cent less material and bears less stress on its joints compared to the seed geometry.

News about the achievement focused on how Dreamcatcher, the generative design application used to create the Elbo chair, heralds the new creative capabilities of computers. Harsuvanakit and Presten , using algorithms to replace some of the aesthetic, material, and construction decisions typically made by humans.

While this story may seem overwhelmingly modern, use of computers in creative work dates back to early days of computation.

Computer-written western

On Oct. 26, 1960, CBS aired an hour-long special entitled The Thinking Machine. Focused on the rise of digital computers and the potential of artificial intelligence, the special also included three short television dramas that had been written by a computer.

The program that 鈥渁uthored鈥 these three western playlets was called SAGA II. It was developed for the by Douglas Ross and Harrison Morse of the Massachusetts Institute of Technology鈥檚 Electronic Systems Laboratory. Ross said while they had a great deal of fun developing the program, their underlying intent was not levity, but to demonstrate the potential for computers to engage in 鈥渃reative鈥 acts.

The Thinking Machine, a 1960 CBS television special, included three short western plays written by artificial intelligence

In the first playlet, a shootout leaves a bank robber mortally wounded. After taking one final drink, the bandit dies, leaving the sheriff to reclaim the money and walk off into the proverbial sunset.

The second playlet is almost identical to the first, but this time the sheriff is mortally wounded instead, leaving the bandit free to escape with his ill-gotten gains. Upon seeing this second iteration, the host of the special, actor David Wayne, said: 鈥淲ell, I can see that there is one thing the computer doesn鈥檛 know 鈥 in television the bad guy is supposed to lose.鈥

Wayne鈥檚 statement highlights key differences between the Elbo chair system and Saga II: Whereas both programs are creative in the sense that they are both producing something novel, the newer Autodesk Dreamcatcher system adds discriminative capacities to the mix.

Empowered machines a transformative technology

SAGA II can at best be described as a blunt instrument of the creative process. Each time the program was run, a new western would be generated. It was then up to the researcher and producers to determine the quality of the script that was produced.

Conversely, Dreamcatcher generated large volumes of possible designs for the Elbo chair but only those that met the parameters established by Presten and Harsuvanakit were shown to the user. As such, one can say that Dreamcatcher was actively considering what made a good design.

There are certainly lessons to be learned by exploring the history of CAD as it relates to our current understanding of creative work, but the generative design demonstrated by the Elbo chair also requires us to come to terms with issues around discrimination.

Actors in the first computer-written western stage a shootout in 1960 as part of the CBS television special on artificial intelligence, The Thinking Machine 

This newfound capacity for determining quality that makes this generative design unique unto itself, and requires us to consider how the line between human expertise and computational systems is changing.

Similar developments in medicine demonstrate the capacity of deep learning systems to diagnose cancer. Venture capitalist Venture capitalists like Khosla see these new computational capacities as increasing the economic abundance and quality of life of humans.

Yet the question remains: What do we lose when we task computational systems with discriminating on our behalf? Other researchers working in the field of oncology have noted ways in which clinical diagnoses serve as a site for explaining how cancer works. These explanations often lead to new medical breakthroughs.

AI researcher of the in Toronto has similarly noted that This has obvious ramifications for medicine.

The impact of these kinds of computational systems in the future is unknown. What is certain however, is that both what it means to be creative, and the roles humans and computers play in that process, are changing.

 is a PhD candidate at U of T. Matt Ratto is an associate professor in U of T's Faculty of Information.

This article was originally published on . Read the .

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