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It involves a custom-built virtual reality enclosure, live flies, and a multiplayer science-fiction shooter arcade game for human and insect participants.

These projects, using sophisticated algorithms to augment human efforts, automate manual tasks, and possibly improve the lives of citizens are towards enforcing Canada's environmental protection laws.

The built environment faces old and new challenges: climate change and natural catastrophes, pollution, water shortage, unemployment, food supply constraints, inefficient infrastructures, living conditions inequalities, short term rent of private houses and subsequent rent increases, displacement of low-middle classes from city centres, empty investment properties, cyber security and surveillance mechanisms, highly educated homeless individuals, privatisation of public spaces, refugee influxes, cultural tensions, extremist groups, populism and unannounced acts of random violence.

Our world is finite, fully explored and with increasing levels of consumption, students expectations to design through massive amounts of materials and human labour will be increasingly difficult to fulfil.

Representations of science and technology in food production practices in science fiction seem to reflect these sentiments, with science and technology portrayed as ‘unnatural’ and therefore ‘bad’.

We contend that scientific interventions are often black boxed and that binary distinctions of ‘natural’ and ‘unnatural’ are unhelpful in promoting constructive conversations about the role of science and technology in food production, as are approaches that rely on ‘education’ to address key fears and concerns.

The concept of “agency” is a popular framework for discussing work with vital (live) materials, often used to imbue them with human qualities such as the capacity for “collaboration”.


Chaired by:  Hidir Aras (FIZ), Linda Andersson (TU Wien) and Allan Hanbury (TU Wien)Website: Dr Hidir Aras (, Dr. Hidir Aras is a research assistant and project manager for text and data mining at FIZ Karlsruhe.

His applied research interests include big data analytics, text and data mining, and semantic analysis of patent information.

Before, after completing his studies in business informatics at the University of Mannheim, he worked for several years at the European Media Laboratory GmbH in Heidelberg on various research projects related to geographical information systems, intelligent mobile assistance and the Semantic Web.

In addition, he was involved in  several EU research projects and leaded the development of a framework of cross-lingual and cross-media semantic annotation and search, which received the 2nd prize in the Semantic Web Challenge  2015 in Bethlehem, USA.

He was scientific coordinator of the EU-funded Khresmoi Integrated Project on medical and health information search and analysis, and is co-founder of contextflow, the spin-off company commercialising the radiology image search technology  developed in the Khresmoi project.

Ms Linda Andersson (, 11 Ms Linda Andersson has for the last 15 years conducted text mining research in close connection to the IP industry.

Ms Andersson has in her PhD research established a generic method for Natural Language Annotation Design for domain-specific text mining solutions for medicine, legal and technical text.

Dr Florina Piroi (, Dr Florina Piroi is a senior researcher at the TU Wien, IFS group, with experience in domain specific search, search engine evaluation and running evaluation campaigns.

She  applied information extraction techniques and natural language processing tools to texts on research articles within the ADmIRE project.

Fast Food Robots, Kiosks, and AI Use Cases from 6 Restaurant Chain Giants

Burger flipping is often used as derogatory shorthand for low-skilled, low-tech work, but fast food companies have been making major investments in automation, apps, analytics, artificial intelligence, and robotics.

We set out to ask the questions that business leaders would need to know: We’ve put together executive quotes and the latest innovations from six of the largest fast food giants on the planet, and distilled them down into this article.

We collected a series of short videos, gifs, and screen-shot images to visually demonstrate the robotics and AI use cases we articulate, so that you’ll be able to see the applications in use, and better understand their potential uses or implications in your own industry.

Before we dive into the robotics and AI use cases from the six fast food giants, it’s important to gain some context on why this industry is keen on innovation now: Rising wages and a need to keep prices low have given several fast food companies a strong incentive to develop technologies to increase efficiency and reduce labor costs.

Wages for fast food companies seem to be being pushed up by two primary causes: At the beginning of the year the minimum wage increased in 19 states.

For example, a recently approved initiative in Washington State will raise the minimum wage to $13.50 an hour by 2020 and last year California adopted a law that will bring the minimum wage to $15 per hour by 2022.

Former McDonald’s USA CEO Ed Rensi told Fox Business that, “It’s cheaper to buy a $35,000 robotic arm than it is to hire an employee who’s inefficient making $15 an hour bagging French fries.” As in any industry, fast food also has a tendency to follow the leader.

The giants of the industry (like the giants in the stodgy automotive industry) are all aware that technology will be a critical edge in the years ahead, and R&D budgets in automation and new customer interfaces reflect this change in attitude.

In addition to app order and payment systems across every possible platform, Domino’s has invested in an artificially intelligent virtual assistant that customers can talk or text.

Domino’s use of integrated GPS tracking for their drivers doesn’t just let the people track their pizza deliveries in real time down to the second, but it also provides the corporation with a wealth of data to improve efficiency and safety.

The very first bullet point in McDonald’s 2017 growth plan is “enhancing digital capabilities and the use of technology to dramatically elevate the customer experience.” The company is planning to make a large push for self-ordering kiosks and mobile app ordering/payment.

When combined with big data analysis, the digital menus can be frequently modified based on time of day or even weather to induce purchases.

The menus are capable of checking the weather and automatically highlight items that do better on hot days or comfort foods when it is cold and rainy.

Tactful executives will not be so overt in their language (Rensi’s candor is aided by the fact that he no longer works at McDonalds), but it’s unlikely that many franchise CEOs will be able to completely ignore robotics in long term planning.

It will cost roughly $15,000 per location, but the company expects the kiosks to pay for themselves in just two years due to the reduced labor costs and increased sales.

Companies are try to push people to order via apps, chat bots, voice recognition, or kiosks instead of from employees behind a counter.

If Amazon handled all your orders over the counter via human cashiers, they’d have a much harder time improving their profits by recommending up-sell and cross-sell products, and fast food companies seem to be catching on.

It is unlikely we will see the person behind the counter disappear in the near term, but companies are invested heavily in the belief that orders taken by machines are going to grow noticeably in the come years, probably along with slowly decreasing need for human staff during business hours.

While fast food companies are particularly sensitive to labor costs and the need to be highly efficient, the general goals behind many of their technology investments are shared by most sectors.

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