Technology transfer for social benefit: Ten principles to guide the process

Figures & data

Table 1. Three-layer model of humans

Level	Functions
Basic	Enables and controls the core functions of life (e.g., nutrition, breath, metabolism, growth, and reproduction). All living beings depend on this level.
Emotional	Enables sensory impressions (e.g., smell, sound, and color) and internal feelings (e.g., fear, anger, and joy). This is the level of animality.
Rational	Comprises the capacities of mind and will and the ability to think, argue, and draw conclusions. In its distinct form, the rational level is only available to humans.

Figure 1. By applying the 10 principles, the social value of technological innovations can be evaluated and guided

Table 2. Possible positive and negative effects of smartphones on all 10 levels. (This paper does not examine and argue the listed individual effects in detail but does illustrate the importance of using a holistic model to realistically assess the interaction of technology with society.)

Individual
Rational	Positive impact Access to knowledge: Smartphones, when combined with the internet, allow for easy and fast access to a universe of information. With an appropriate attitude, smartphone users can expand their knowledge quickly. Negative impact Mental laziness: An increase in the number of cognitive tasks being transferred to smartphones has been observed. There is a threat that excessive use of mobile devices may lead to mental laziness (Barr et al., 2015).
Emotional	Positive impact Promoting creativity: Smartphones can be used to cultivate curiosity, nourish the imagination, snap photos of mundane objects, or document ideas. In that manner, smartphones can be used as creativity-enhancing tools. Negative impact Distraction: Smartphones cause massive distraction from the real world if constantly used (Duke et al., 2018; Stothart et al., 2015). Distancing from reality in this manner can promote unhealthy emotions such as fear and narcissism (Hussain et al., 2017; Lee et al., 2014).
Basic	Positive impact Health monitoring: Smartphone use can promote a healthier lifestyle, for example, by tracking the user’s amount of movement, nutrition, or blood pressure. Negative impact Health hazard: Excessive smartphone use can negatively affect health because of, for example, exposure to electromagnetic radiation and blue light, and cause poor posture, its resulting neck stiffness, or damage to vision.
Society
Trusting Relationships		Positive impact Strengthen bonds: Smartphones help users stay in touch with family and friends worldwide, facilitate continuous communication, and thus strengthen and support social relationships. Negative impact Emotional neglect: Excessive smartphone use can impair and endanger interpersonal relationships (Elsobeihi & Abu Naser, 2017) and has a particularly critical effect on small children. When parents are absorbed by their smartphones, children may experience emotional problems.
Meaningful Business		Positive impact New business: Smartphones create many new opportunities for companies, for example, smartphone manufacturers, app development companies, and internet service providers. Negative impact Increased stress: The constant accessibility made possible by smartphones can also easily lead to increased stress. Research has confirmed that the intrusion of smartphones into daily life can significantly endanger a healthy work–life balance (Harris, 2014).
Freedom		Positive impact Freedom: Smartphones offer new freedoms to do what an individual thinks is important, for example, phone booths are obsolete, and research can be conducted online from home, instead of at the library. Negative impact Addiction: Smartphone addiction is a substantial problem. A meta-analysis demonstrated that approximately 25% of children and teenagers demonstrate signs of smartphone addiction (Sohn et al., 2019).
Justice		Positive impact Exposing injustices: Smartphones have capabilities, such as video, that can help victims and expose injustices. For example, bystanders recorded the police killing of George Floyd in the United States, and the videos were broadcast on the news and used as evidence in court (Rowley, 2015). Negative impact Sweatshop labor: The production of smartphones can be problematic, for example, child or enslaved labor and toxic factories without safety equipment (Cooper, 2018; Bloomberg News, 2018; Lee, 2016).
Peace		Positive and negative impact Smartphones can be used, for example, to build a peaceful world and to endanger it, or communicate affection and goodwill or glorify hatred and violence. The availability of smartphones makes it easier to organize collective activities, peaceful and violent (Pierskalla & Florian Hollenbach, 2013).
Planet
Biosphere	Positive impact Wildlife preservation: Smartphones can be used to monitor and protect wildlife such as the poaching of African elephants (Wall, 2014). Negative impact Electropollution: Ecosystems are under the constant influence of high-frequency radiation from smartphone antennas. Behavioral changes in and damage to insects, birds, and other animals have been reported (Rafiqi et al., 2016).
Resources	Positive impact Raising awareness: Smartphones enable real-time documentation and communication. This effect can be used to protect the environment, for example, in 2013, when the Pegasus pipeline in Arkansas burst and the residents documented the resulting damage (Sheppard, 2013). Negative impact Wasted resources: Smartphones are one of the most resource-intensive products on the market, containing precious metals and rare earths. The production of smartphones causes an enormous consumption of these valuable elements, and an estimation is that approximately 10 million smartphones are discarded or replaced each month in the European Union (Gabbatiss, 2019).

Table 3. Presents arguments for and against the deployment of Golden Rice. Because of the opposing views, the table does not present positive or negative effects

Individual
Rational	The mind is the essential tool with which the effects—and the possible side effects—of a technology can be assessed. Reason asks for facts and draws logical conclusions. However, both sides—proponents and opponents—present data to support their views.
Emotional	The debate on Golden Rice is very emotional. Prominent proponents write that millions of children are unnecessarily blinded because Golden Rice is not being introduced to their diet (Potrykus, 2013). The delay in the introduction of Golden Rice was even called a ‘silent holocaust’ (Chassy, 2010). Opponents are destroying field trials because they believe this method is the only way to maintain food sovereignty (Kupferschmidt, 2013).
Basic	The aim of Golden Rice is to remedy basic nutritional deficiencies that lead to serious diseases. It is therefore on the basic level. Proponents argue that Golden Rice is an effective aid to alleviate the problem (Tang et al., 2009) and that no risks are associated with this technology (Golden Rice Project kein Datum). Opponents argue that the yield of carotenoids in Golden Rice is far too low (they base their argument on field studies) (Grain, Masipag and Stop Golden Rice! Network, 2018). Therefore, Golden Rice will not be a solution to vitamin A deficiency (Grain, Masipag and Stop Golden Rice! Network, 2018). Furthermore, whether the rice is safe is in doubt (Stone & Glover, 2016).
Society
Trusting Relationships	Opponents argue that social and cultural barriers to Golden Rice must also be considered. For example, white rice (as opposed to yellow rice) has high cultural value. Technological projects have often failed because a gap between science and local communities has not been bridged (Kettenburg et al., 2018).
Meaningful Business	Proponents argue that Golden Rice is an efficient solution to a major problem (Mayer et al., 2006). The critics, however, posit that planting gardens with fruit and vegetables would be a far more cost-effective method.
Freedom		Is the freedom of local farms restricted by Golden Rice? Opponents fear that small farmers will become dependent on agrotech companies and lose their freedom to grow and promote their rice varieties. Proponents argue that this case will not occur and that cultivation will only be approved by regional authorities and independent rice research institutes (Mayer et al., 2006).
Justice		Proponents argue that refusing to allow the poor to benefit from modern agro-technology is irresponsible. Opponents consider Golden Rice a fake quick fix because the urgency to ameliorate the underlying poverty would be veiled and a quest for social justice would be prevented (Kettenburg et al., 2018).
Peace		The intensity of the conflict over Golden Rice (and GMOs is agriculture in general) is so serious that it has been compared with war (Lang & Heasman, 2004).
Planet
Biosphere		Would growing Golden Rice endanger traditional rice varieties? Opponents fear genetic contamination, leading to losing native and regionally adapted varieties and reducing biodiversity (Kettenburg et al., 2018). Proponents argue that a possible gene flow from Golden Rice to wild varieties would be very low. However, even then, they would be quickly thinned out because the carotenoid genes would not have a selective advantage (Golden Rice Project kein Datum).
Resources (abiotic components)		Opponents ask how Golden Rice will influence the abiotic components of ecosystems. Will more fertilizers, pesticides, and irrigation be required than for wild plants? Notably, irrigated rice cultivation is responsible for a considerable amount of methane emissions (Kettenburg et al., 2018).

Table 4. A selection of possible effects of AI on society. Because the technology has been used for a short time, but is developing rapidly, this table refers to opportunities and risks

Individual
Rational	Chances Improving learning: AI could potentially improve individual learning through personalization. A pilot study demonstrated how AI-based training programs can improve cognitive performance (Kee et al., 2019). Risks Loss of rational overview: In many cases, AI algorithms cannot be explained, because how the results are obtained remains unknown. Thus, it is difficult—or impossible—for human reasoning to determine whether the decisions made by AI are justified (Herweijer & Waughray, 2018).
Emotional	Chances Helping the blind: AI could potentially make life easier for the visually impaired through navigation aids, providing a richer and deeper understanding of their surroundings, including the recognition of other people (Chui et al., 2018). Risks Distrust in reality: With AI technologies such as Deepfake (a portmanteau of ‘deep learning’ and ‘fake’), individuals might have increasingly less trust in their senses. For example, when they view video content that depicts an event (e.g., a political speech) that did not occur (Howard, 2019).
Basic	Chances Improved health: AI technologies can be valuable support in maintaining or achieving health, for example, fitness training, personalized medical treatments, or improved diagnosis (e.g., cancer) (Crawford et al., 2019; Bughin et al., 2019, p. 26). Risks Compromised safety: AI can be hacked to harm people, or autonomously decisive AI algorithms can lead to dangerous results (e.g., in autonomous vehicles) (Herweijer & Waughray, 2018) (Crawford et al., 2019).
Society
Trusting Relationships		Chances Understanding fellow humans: With AI tools, attempts have been made to overcome the emotional difficulties of understanding autism. The aim is to help children with autism to better understand how other people feel (Marwan, 2018; McManus, 2017). Risks Pseudo relationships: Machines are becoming increasingly human-like and can seemingly replace human interactions, for example, Akihiko Kondo, in Japan, took a virtual hologram, a comic figure, as his wife (Paulo, 2019; Hegarty, 2019).
Meaningful Business		Chances Undoubtedly, AI will improve the efficiency of businesses, for example, predictive maintenance, where service parts and machines are repaired or replaced at the optimum time, namely, before they fail (Barnard, 2019). Risks Abusing power over employees: AI systems can be used to comprehensively monitor employees. Today, such systems are used to automatically assess employees’ performances, set performance targets, and initiate dismissals (Crawford et al., 2019).
Freedom		Chances More freedom: The old question of whether machines lead to more freedom or more coercion of humans is condensed in the judgment about the effect of AI. Proponents of the AI technologies see this as a positive development liberating people from routine work, allowing them to pursue their own interests. There is no reason that standard work week cannot be halved in the future as productivity increases due to AI (Spyros, 2017). Risks Endangered freedom: When algorithms are increasingly making the most important decisions, and when governments and companies monitor an increasing amount of citizens and customers with AI systems, human freedom is at high risk (Crawford et al., 2019).
Justice		Chances Justice will be more affordable: AI has the potential to improve the quality and efficiency of the judicial system because substantial amounts of information could be analyzed more efficiently, possibly making the public civil justice system more affordable (Wu, 2019). Risks Mindless law: The critical question is whether only humans (and not AI) can distinguish between what is morally good and bad, and thus able to interpret the law correctly (Davis, 2018).
Peace		Nations are vying to become the leading power in autonomous weapons, for example, military drones, automated combat aircraft, and robotic soldiers are already in use. The increase in destructive power that technology provides is far beyond the imagination.
Planet
Biosphere	Chances Habitat conservation: The use of AI opens new possibilities for monitoring and conservation of habitats, which should prevent, for example, trade of wild animals (Herweijer & Waughray, 2018). Risks Loss of biodiversity: If agriculture is only geared toward short-term production efficiency—and AI-driven agriculture could take this to the extreme—agricultural landscapes will be exposed to even more pesticides and fertilizers, leading to leached soil and soil erosion and a further loss of biodiversity.
Resources	Chances Improving recycling: The modern era is creating too much waste. To increase the recycling of dumped products, AI-assisted robots are being developed that are better than humans at sorting waste in processing plants (Ioannou & Petrova, 2019). Risks Massive carbon footprint: AI models require massive computing resources to process large training datasets. Thus, technology is a major factor in the further increase of greenhouse gas emissions (Strubell et al., 2019).

Figure 2. To achieve social value through technology, the two classic drivers of innovation, namely, technology push and market pull, are now insufficient. A third dimension is necessary—we call it good world design—which helps align technical progress with social welfare

Table 5. Exemplary targets for better designed smartphones (derived from the 10 principles)

Individual
Emotional	Goal: Reduction of addictive behavior Social media and news feeds are designed to attract and retain users. Digital over-consumption is therefore encouraged but not prevented. This problem must be addressed on the hardware and software sides (and connected with business models). The ‘Lightphone,’ for example, is designed to be used as little as possible (The Light Phone, 2019). It should serve the user, not the other way round. At the software level, many apps have been developed for ‘digital detoxification,’ which should help reduce individuals’ continuous connection to their smartphones (Van Harald, 2015; Menthal, 2019; Hold, 2019; FamilyTime, 2019).
Society
Freedom	Goal: Ensuring privacy For an increasing number of activities, society is depending on smartphone apps. The further processing of personal data by these tools often leads to an invasion of the user’s privacy. With the appropriate attitude, however, apps can be designed to reduce access to sensors (location, motion, camera, microphone) and locally stored data (pictures, contacts) to an absolute minimum (European Union Agency For Network and Information Security, 2017).
Planet
Resources	Goal: Reducing e-waste On average, consumers replace their smartphones every two years. Discarded smartphones worldwide are dumped into landfills in Africa and Asia, demonstrating the dirty side of digitization. Smartphones must therefore be designed to last longer and be repairable when necessary, requiring new design methods that support easy disassembly and a secondhand market for smartphones (Michel, 2018).

Table 6. Key requirements for AI design, as a basis for enabling social value creation

Individual
Rational	Requirement: AI must be controlled by humans AI can fulfill many functions of humans. As a result, citizens will increasingly be subject to decisions made by AI systems. It is therefore essential that AI systems are designed to support and enhance human cognitive abilities, not to advance beyond them. AI should complement cognitive abilities, but not replace them. Thus, AI must never have final and complete control because it can always be overridden by humans. EU requirement 1: human agency and oversight EU requirement 7: accountability
Emotional	Requirement: AI must be recognizable AI is becoming increasingly capable of imitating reality; thus, it must be ensured that the individuals who perceive reality through their senses can assign it as such. For example, it must be possible to recognize whether a video documents a real process or whether it was produced synthetically (cf. “Deepfake”), or whether a voice on the telephone belongs to a person or a chatbot.
Basic	Requirement: AI must not cause harm AI technologies can pose new security risks to users when embedded in products and services. For example, a stand-alone car can incorrectly identify an object on the road, because of a flaw in object recognition technology, causing an accident with injuries and property damage (European Commission, 2020). AI systems must be designed to be safe, reliable, and robust so that they can safely manage errors and inconsistencies.^4 If a system is compromised, it must be possible for human control to take over and abort the system. EU requirement 2: robustness and safety
Society
Trusting Relationships		Requirement: AI must support healthy human–human relationships AI enables the increasingly complete observation of individuals; social scoring systems evaluate how “good” citizens are. AI-activated surveillance systems that infiltrate the lives of individuals and thus affect human relationships are extremely dangerous and would massively undermine a healthy, trusting relationship between individuals in society.
Meaningful business		Requirement: AI must enhance meaningful work AI systems will fundamentally change the world of work. They should support workers in their working environment and aim to create meaningful work. However, a real danger is that technology will deprive people of their uniqueness and treat them like objects. The development of AI technologies requires a greater awareness of how technology can complement rather than reduce meaningful work (Comission & High- Level Expert Group on Artificial Intelligence, 2019).
Freedom		Requirement: AI must respect human autonomy AI increases the possibilities to follow and analyses daily habits. For example, AI could be used by employers to monitor employees’ behavior (European Commission, 2020). However, AI systems must respect the freedom and autonomy of the individual, and this includes that citizens should have full control over their data. AI systems must be designed to ensure privacy and freedom. EU requirement 3: privacy and data governance
Justice		Requirement: AI must be fair The overall goal of the development, introduction, and use of AI systems must be fairness. Special attention must therefore be paid to AI applications that would exacerbate power or information asymmetries, such as those between businesses and consumers or between governments and citizens (Comission & High- Level Expert Group on Artificial Intelligence, 2019). The advantages and disadvantages of AI systems must be evenly distributed among the various population groups, and the weak and vulnerable must receive special protection. EU requirement 5: diversity, non-discrimination, and fairness
Peace		Requirement: Autonomous weapons should be banned The defense industry is a strong driver of innovation, for example, autonomous lethal weapons. Such weapons systems fight targets without human intervention and fully automate lethal damage. Notably, in the most diverse national and corporate guidelines for the development of ethical AI, the enormous importance of peace efforts remains almost unarticulated. However, what must be ensured is that AI must not be allowed to start inhuman wars.
Planet
Biosphere	Requirement: AI must not endanger (habitats of) other species With the help of AI, humans can realize their demands on space and resources more efficiently. Thus, of central importance in the design of AI is to consider and protect the right to life of fellow beings.
Resources	Requirement: Enhance sustainability AI-controlled precision agriculture could enable the early detection of plant diseases and thus reduce the consumption of pesticides (Herweijer & Waughray, 2018); however, it can also be used to further exploit the soil by further eliminating accompanying plants and organisms if the soil is only considered as a production factor and not as a living ecosystem with inherent value. AI systems must therefore be designed to enhance sustainability. EU requirement 6: societal (relates to all social principals) and environmental well-being (relates to both planet principles)

Barr, N., Pennycook, G., Stolz, J. A., & Fugelsang, J. A. (2015). The brain in your pocket: Evidence that smartphones are used to supplant thinking. Computers in Human Behaviour, 48, 473–480. https://doi.org/10.1016/j.chb.2015.02.029

 Web of Science ®Google Scholar

Duke, K., Ward, A., Gneezy, A., & Bos, M. (2018). Having Your Smartphone Nearby Takes a Toll on Your Thinking. Harvard Business Review, March 20. Retrieved December 8, 2019, from https://hbr.org/2018/03/having-your-smartphone-nearby-takes-a-toll-on-your-thinking

 Google Scholar

Stothart, C., Mitchum, A., & Yehnert, C. (2015). The attentional cost of receiving a cell phone notification. Journal of Experimental Psychology. Human Perception and Performance, 41(4), 893–897. https://doi.org/10.1037/xhp0000100

 PubMed Web of Science ®Google Scholar

Hussain, Z., Sheffield, M. D., & Griffiths, D. (2017). An investigation into problematic smartphone use: The role of narcissism, anxiety and personality factors. Journal of Behavioral Addictions, 6(3), 378–386. https://doi.org/10.1556/2006.6.2017.052

 PubMed Web of Science ®Google Scholar

Lee, H., Heejune, A., Choi, S., & Choi, W. (2014). The SAMS: Smartphone addiction management system and verification. Journal of Medical Systems, 38(1), 1. https://doi.org/10.1007/s10916-013-0001-1

 PubMed Web of Science ®Google Scholar

Elsobeihi, M. M., & Abu Naser, S. S. (2017). Effects of mobile technology on human relationships. International Journal of Engineering and Information Systems, 1(5), 110–125. https://www.researchgate.net/publication/319212701_Effects_of_Mobile_Technology_on_Human_Relationships/citation/download

 Google Scholar

Harris, T. R. (2014). The Impact of Smartphones on Work-Life Balance. Master Thesis, Middle Tennessee State University.

 Google Scholar

Sohn, S., Rees, P., Wildridge, B., Kalk, N., & Carter, B. (2019). Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: A systematic review, meta-analysis and GRADE of the evidence. BMC Psychiatry, 19(1), 356. https://doi.org/10.1186/s12888-019-2350-x

 PubMed Web of Science ®Google Scholar

Rowley, J. M. (2015). The quest for social justice goes mobile. Fast Company, February 19. https://www.fastcompany.com/3041445/the-quest-for-social-justice-goes-mobile

 Google Scholar

Cooper, D. (2018). You can’t buy an ethical smartphone today. Engadget, February 6. https://www.engadget.com/2018-02-06-ethical-smartphone-conscious-consumption.html

 Google Scholar

Bloomberg News. (2018). Apple Supplier Workers Describe Noxious Hazards at China Factory.” Bloomberg, January 16. https://www.bloomberg.com/news/articles/2018-01-16/workers-at-apple-supplier-catcher-describe-harsh-conditions

 Google Scholar

Lee, Y. (2016). 2 words keep sick Samsung workers from data: Trade secrets. Associated Press, August 11. https://apnews.com/article/ea1b8280b50b4ad3a9bdcd9def798914

 Google Scholar

Pierskalla, J. H., & Florian Hollenbach, M. (2013). Technology and Collective Action: The Effect of Cell Phone Coverage on Political Violence in Africa. American Political Science Review, 107(2), 207–224. https://doi.org/10.1017/S0003055413000075

 Web of Science ®Google Scholar

Wall, J. (2014). Technology solutions for wildlife conservation: How GPS and cell phones are helping to monitor and protect African elephants. Save the Elephants, May 30. https://www.savetheelephants.org/about-ste-2/press-media/?detail=technology-solutions-for-wildlife-conservation-how-gps-and-cell-phones-are-helping-to-monitor-and-protect-african-elephants

 Google Scholar

Rafiqi, S., Kumar, S., & Chaudhary, R. (2016). Mobile Phone radiations and its impact on birds, animals and human beings. Trends in Veterinary and Animal Sciences, 3, 24–27. http://jakraya.com/journal/pdf/3-tvasArticle_7.pdf

 Google Scholar

Sheppard, K. (2013). Reporters Say Exxon Is Impeding Spill Coverage in Arkansas. Mother Jones Daily, April 5. https://www.motherjones.com/politics/2013/04/reporters-say-exxon-impeding-spill-coverage-arkansas

 Google Scholar

Gabbatiss, J. (2019). ‘Endangered’ elements used to make mobile phones are running out quickly, scientists warn. Independent, January 22. https://www.independent.co.uk/news/science/mobile-phones-elements-periodic-table-endangered-chemicals-st-andrews-a8739921.html

 Google Scholar

Potrykus, I. (2013). Genetic modification and the public good. European Review, 21(S1), 68–79. https://doi.org/10.1017/S1062798713000203

 Web of Science ®Google Scholar

Chassy, B. (2010). Food safety risks and consumer health. Nature Biotechnology, 27(5), 534–544. https://doi.org/10.1016/j.nbt.2010.05.018

 Google Scholar

Kupferschmidt, K. (2013). Activists Destroy ‘Golden Rice’ Field Trial. August 9. https://www.sciencemag.org/news/2013/08/activists-destroy-golden-rice-field-trial

 Google Scholar

Tang, G., Qin, J., Grusak, G. D., Dolnikowski, M. A., & Grusak, M. A.. (2009). Golden rice is an effective source of vitamin A. The American Journal of Clinical Nutrition, 89(86), 1776–1783. https://doi.org/10.3945/ajcn.2008.27119

 PubMed Web of Science ®Google Scholar

Grain, Masipag, and Stop Golden Rice! Network. (2018). Don’t get fooled again! Unmasking two decades of lies about golden rice. GRAIN, November 21. https://www.grain.org/es/article/6067-don-t-get-fooled-again-unmasking-two-decades-of-lies-about-golden-rice

 Google Scholar

Stone, G. D., & Glover, D. (2016). Disembedding grain: Golden rice, the green revolution, and heirloom seeds in the Philippines. Agriculture and Human Values, 34(1), 87–102. https://doi.org/10.1007/s10460-016-9696-1

 Web of Science ®Google Scholar

Kettenburg, A. J., Hanspach, J., Abson, D. J., & Fischer, J. (2018). From disagreements to dialogue: Unpacking the golden rice debate. Sustainable Science, 13(5), 1469–1482. https://doi.org/10.1007/s11625-018-0577-y

 PubMed Web of Science ®Google Scholar

Mayer, J. E., Beyer, P., & Potrykus, I. (2006). The Golden Rice Project. Biotechnology, 23, 482–487. http://www.goldenrice.org/PDFs/The_Golden_Rice_Project_Mayer_et_al_2006.pdf

 Google Scholar

Lang, T., & Heasman, M. (2004). Food wars: The global battle for mouths, minds and markets. Earthscan.

 Google Scholar

Kee, T., Weiyan, C., Blasiak, A., Peter Wang, J. K., Chong, J. C., Thomas Yeo, B. T., Dean, H., & Asplund, C. L. (2019). Harnessing CURATE.AI as a Digital Therapeutics Platform by Identifying N-of-1 Learning Trajectory Profiles. Advanced Therapeutics, 2(9), 1900023. https://doi.org/10.1002/adtp.201900023

 Google Scholar

Herweijer, C., & Waughray, D. (2018). Fourth Industrial Revolution for the Earth. Harnessing Artificial Intelligence for the Earth. PricewatershouseCoopers (PwC).

 Google Scholar

Chui, M., Harryson, M., Manyika, J., Roberts, R., Chung, R., van Heteren, A., & Nel, P. (2018). Notes from the AI frontier: Applying AI for social good. McKinsey & Company.

 Google Scholar

Howard, A. (2019). The Regulation of AI — Should Organizations Be Worried? MIT Sloan Management Review, July 29. Retrieved December 5, 2019, from https://sloanreview.mit.edu/article/the-regulation-of-ai-should-organizations-be-worried

 Google Scholar

Crawford, K., Dobbe, R., Dryer, T., Fried, G., Green, B., Kaziunas, E., Kak, A., et al. (2019). AI Now 2019 Report. AI now Institute.

 Google Scholar

Bughin, J., Hazan, E., Allas, T., Hjartar, K., Manyika, J., Sjatil, P. E., & Shigna, I. (2019). Tech for Good: Smoothing disruption, improving well-being. McKinsey Global Institute (MGI).

 Google Scholar

Marwan, S. (2018). Rana El Kaliouby CEO Of Affectiva Is Training Robots To Read Feelings. Forbes, November 29. https://www.forbes.com/sites/samarmarwan/2018/11/29/affectiva-emotion-ai-ceo-rana-el-kaliouby/#79e859c21572

 Google Scholar

McManus, A. (2017). Brain Power Launches Much Anticipated Emotion-Enabled Autism System for Smart Glasses. Affektiva, July 11. https://blog.affectiva.com/brain-power-launches-much-anticipated-emotion-enabled-autism-system-for-smart-glasses

 Google Scholar

Paulo, D. A. (2019). How AI is coming ‘alive’, replacing human roles — As robots or as wives. can Insider, October 6. Retrieved December 12, 2019, from https://www.channelnewsasia.com/news/cnainsider/how-ai-is-coming-alive-replacing-human-roles-as-robots-or-wives-11973644

 Google Scholar

Hegarty, S. (2019). Why I ‘married’ a cartoon character. Retrieved August 16, 2020, from https://www.bbc.com/news/stories-49343280

 Google Scholar

Barnard, A. (2019). First Aid on Tracks. Siemens, January 22. https://new.siemens.com/global/en/company/stories/research-technologies/artificial-intelligence/artificial-intelligence-ai-for-rail.html

 Google Scholar

Spyros, M. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. https://doi.org/10.1016/j.futures.2017.03.006

 Web of Science ®Google Scholar

Wu, J. (2019). AI Goes to Court: The Growing Landscape of AI for Access to Justice. Medium, August 6. https://medium.com/legal-design-and-innovation/ai-goes-to-court-the-growing-landscape-of-ai-for-access-to-justice-3f58aca4306f

 Google Scholar

Davis, J. P. (2018). Law without mind: AI, ethics, and jurisprudence. California Western Law Review, 55(1), 165–219. https://doi.org/10.2139/ssrn.3187513

 Google Scholar

Ioannou, L., & Petrova, M. (2019). America is drowning in garbage. Now robots are being put on duty to help solve the recycling crisis. CNBC. July 27. https://www.cnbc.com/2019/07/26/meet-the-robots-being-used-to-help-solve-americas-recycling-crisis.html

 Google Scholar

Strubell, E., Ganesh, A., & Andrew, M. (2019). Energy and policy considerations for deep learning in NLP. In 57th. Annual Meeting of the Association for Computational Linguistics, 6.

 Google Scholar

The Light Phone. (2019). The Light Phone. The Light Phone. Retrieved December 9, 2019, from https://www.thelightphone.com

 Google Scholar

Van Harald, C. (2015). Diese App hilft gegen Smartphone-Sucht. WeLT, September 19. Retrieved December 15, 2019, from https://www.welt.de/wirtschaft/webwelt/article146354066/Diese-App-hilft-gegen-Smartphone-Sucht.html

 Google Scholar

Menthal. (2019). Menthal Balance. Menthal, Retrieved December 3, 2019, from https://menthal.org

 Google Scholar

Hold. (2019). Hold. Retrieved December 7, 2019, from https://www.hold.app

 Google Scholar

FamilyTime. (2019). FamilyTime. Retrieved December 12, 2019, from https://familytime.io

 Google Scholar

European Union Agency For Network and Information Security. (2017). Privacy and Data Protection in Mobile Applications. European Union Agency for Network and Information Security.

 Google Scholar

Michel, E. (2018). Secondhand smartphone market takes off but far from green. Phys Org, February 27. Retrieved December 8, 2019, from https://phys.org/news/2018-02-secondhand-smartphone-green.html

 Google Scholar

European Commission. (2020). WHITE PAPER: On Artificial Intelligence. A European Approach to Excellence and Trust.

 Google Scholar

Comission, E. U., High- Level Expert Group on Artificial Intelligence. (2019). Ethics Guidelines For Trustworthy AI. European Commission, April 8. https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai

 Google Scholar