Generative AI is poised to have a transformative impact on society and the workforce across several dimensions:

1. Automation and Efficiency: Generative AI can automate routine and repetitive tasks, which could lead to increased efficiency in various industries. For example, in journalism, AI can write standard reports, allowing human journalists to focus on in-depth investigative work. In design, AI can generate initial models, speeding up the creative process.
2. Job Displacement and Creation: While there is a concern that AI could displace jobs, particularly in sectors reliant on routine tasks, it also has the potential to create new types of jobs. These could include roles in AI management, oversight, and development, as well as new opportunities in industries that harness AI to offer new services or products.
3. Education and Skill Development: The rise of generative AI emphasizes the need for a workforce skilled in AI literacy, data analysis, and ethical considerations surrounding AI use. Educational systems may need to adapt to prepare individuals for these new demands, focusing more on critical thinking, creativity, and technical skills.
4. Ethical and Societal Considerations: Generative AI raises significant ethical questions, such as biases in AI outputs, the potential for misuse (e.g., deepfakes), and privacy concerns. Addressing these issues will require robust regulatory frameworks and ongoing dialogue among stakeholders to ensure that AI is used responsibly.
5. Economic Impact: AI could drive economic growth by creating new market opportunities and increasing productivity. However, it could also exacerbate economic disparities if the benefits of AI are unevenly distributed or if there is a significant divide between those who have the skills to work with AI and those who do not.
6. Cultural and Creative Fields: In creative sectors, generative AI can be both a tool and a collaborator, helping to push the boundaries of art, music, and literature. However, it also prompts discussions about the nature of creativity and originality.
7. Healthcare: In healthcare, AI can help diagnose diseases more accurately and quickly, recommend personalized treatment plans, and automate administrative tasks, potentially improving care outcomes and efficiency.

The impact of generative AI will be broad and multifaceted, requiring proactive adaptation from individuals, businesses, and governments to harness its benefits while mitigating its risks.

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Ever imagined how we type and scroll through one website and get thousands of recommendations on similar topics on other media platforms? In the digital world, the process of digitisation has been optimised through the Big Data Revolution. It is now considered as the ‘New Gold’. Based on ‘one like’ a person’s personal choices ranging from clothes, food, politics everything could be analysed and enumerated. This data is then used by companies to sell the apt products or services based on our preferences. We are dependent on various applications for booking appointments, paying bills and also to make some quick decisions for instance, finance, insurance or stock management.  The life between online and offline has been significantly blurred and is now present in almost all aspects of our life.

This reminds me of an architectural design made by the 18th-century philosopher Jeremy Bentham. It was an annular building on the periphery, at the centre there was a tower with large windows opening towards the inner side of the ring. The inner structure was divided into small cells with two windows. One corresponds to the tower and another allows light to pass across the hall. And by placing one supervisor, a principal, or an inspector at the centre of the tower it could turn into a mental asylum, a school, or a prison. Michael Foucault in his work ‘ Discipline and Punish: The Birth of the Prison’ uses this Panopticon model to explain the Genesis of power. The entire system is a visual trap. The person in the cell would never know whether somebody is watching them or not. Power in this design becomes ‘unverifiable’. Anyone can gaze through the tower thus a capillary action of power is created rather than a single unit of power. Bentham devised this idea for disciplinary purposes in several institutions.

Today panopticism as a metaphor can be used to define technological surveillance. Since power is exercised over us and our decision-making is invisible and unverifiable we do not explicitly feel being violated. While downloading an app, or giving acceptance to certain access on our phone we do not analyse the consequences of it. As our human mind is conditioned to focus on results and to maximise desires, we tend to ignore threats that are certainly looming over us all the time. George Orwell’s ‘Big Brother’ is now transformed into an invisible power wherein our choices and rights are not limited, we are not living in an authoritarian state rather we are living in a state of illusion. Data is Controlling our search optimisation techniques.

After the infamous revelation of the surveillance system of United States investigative agencies by the whistleblower Edward Snowden, people and scholars started to identify the ethical issues surrounding privacy, big data, and Governance. Further, after the US Presidential elections in 2016, this concern was alleviated by a controversy. Scholars have termed this kind of technology as persuasive technology. Digital panopticism is controlling and changing our behavioural patterns.

Many countries have now adopted digital media codes or rules and regulations to restrict the misuse of the data collected by various online platforms. In India, the recent Information Technology (IntermediaryGuidelines and Digital Media Ethics Code) Rules 2021 is also laid down on similar lines. The government has described these rules as a soft-touch self-regulatory mechanism. All media platforms will have to set up a grievances redressal and compliance mechanism, which should constitute a resident grievance officer, chief compliance officer, and a nodal contact person. The Ministry of Electronics & Information Technology has further ordered platforms to submit monthly reports on complaints received from users and actions taken. Finally, instant messaging apps will have to make provisions  for tracking the first originator of a message in case it is asked by legitimate authorities. Apprehensions raised by companies are related to the latter part of the rule.

Media platforms will have to accept the rules for the greater good. However, both sides will have to reconcile and find a middle way by ensuring safety to the citizens. On the other hand, specific rules will have to be laid down as to stating the purpose of tracking messages and how the data will be utilised.

The government’s initiative is timely as technology is outgrowing the legal-justice system. The new era is going to be the age of the digital world, however ethical themes as enshrined in international treaties and our constitution must always be upheld. Human dignity and right to privacy as under Fundamental Rights and the Universal Declaration of Human Rights (UDHR) must guide the policies and actions of various entities. Values such as autonomy, equal power relationships, and control over technology are not explicitly named in the treaties but can be seen as part of following these fundamental and human rights.

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Artificial Intelligence is widening its reach to different strata of our life. From the personalized ads to health care facilities, the presence of AI is felt everywhere. Therefore, it is only imperative that we have a thorough understanding of a technology that is growing to become a major part of our lives. This underscores the necessity to be well-versed in the ethics of artificial intelligence, the relevance of which is unquestionable.

What are Ethics?

Ethics of AI refers to those values and principles that act as a torch while we traverse through the hazy paths of advancing technologies like machine translation, facial recognition, or streaming services that run on recommendation algorithms. According to Anna-Mari Rusanen(University lecturer, cognitive science, University of Helsinki), the need for AI literacy becomes all the more important considering the fact that “we are all already parts of various AI systems, and they are developing rapidly.”

As the impact, artificial intelligence has on us is on the rise, it is important to have clarity about what we are dealing with and the ethical questions that come with it.

1. Identification Of Technology

It is important to make a distinction between the aspects of technology that requires reaction and response. Artificial intelligence is a part of even minute segments of our life. It is present wherever there is a requirement of efficiency and accuracy to manage monumental amounts of data. The field of health care is being taken up a notch by the technology that is capable of detecting even the most subtle flaws or errors that will miss the human eye. While on the defense landscape, speculations and discussions are on the table regarding the competence and capability of artificial intelligence in combat. The part it plays on social media platforms is evident without special mention.

This is where we must draw a line between risks and benefits, the inherent risks that can often lead to violation of privacy or human rights. We must be wise and knowledgeable to understand when the technology violates the line of control of privacy and interferes with the inner chambers of our lives.

Technology as we already know is not inherently good or bad. It is about how we use it and for what purpose. Therefore, as users, it is our responsibility to be on guard and ensure that technology doesn’t break the ethical walls in a bid to spread its branches all over the world and our world.

2. The Changing Ethics

Artificial intelligence is a technology with immense scope and possibilities. When the AI filter is added to any field, it enhances the clarity of functions, boosting it to progress and grow. However, it is also necessary to decide what kind of technologies must be used and to ensure that the technologies chosen are in sync with human rights and principles. A new solution can even be a deciding factor in the relationship between a state and its citizen.

According to Rusanen,

“Politicians and the people creating actual AI solutions must consider surprisingly profound questions regarding things like the nature of the default citizen around whom AI-based public services are organized.”

The draft on AI regulations to be released by the EU is proof that politicians have realized this important factor. These regulations will give a clear list of what can be done and what cannot be done using the technology with a firm emphasis on human rights. A clear line of distinction will be drawn between what is useful and what is abusive thereby placing AI within a suitable ethical framework.

3.Ethics Are Not Mere Icing On The Cake

It is important for organizations to realize that ethics is not just namesake signing off a document at the end of a deal. Rather they are concrete frameworks that must be in place. Companies must have a clear picture regarding how AI-centered technologies they use will impact the customers.

In the words of Rusanen,

“Developers must think about to whom their product or service is relevant, how the rights of these people are protected, and what consequences they may face. Everyone working with artificial intelligence must acknowledge what the ethical principles actually mean for their daily work. This must be done at each design meeting and it must guide the process from its very beginning. It’s not enough for an ethical advisor to sign off on the end result.”

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As dispute over research, diversity grows.

Google fired staff scientist Margaret Mitchell on Saturday, they both said, a move that fanned company divisions on academic freedom and diversity that were on display since its December dismissal of AI ethics researcher Timnit Gebru.

Google said in a statement Mitchell violated the company’s code of conduct and security policies by moving electronic files outside the company.

Mitchell, who announced her firing on Twitter, did not respond to a request for comment.

Google’s ethics in artificial intelligence work has been under scrutiny since the firing of Gebru, a scientist who gained prominence for exposing bias in facial analysis systems.

The dismissal prompted thousands of Google workers to protest.

She and Mitchell had called for greater diversity and inclusion among Google’s research staff and expressed concern that the company was starting to censor papers critical of its products.

Gebru said Google fired her after she questioned an order not to publish a study saying AI that mimics language could hurt marginalised populations.

Mitchell, a co-author of the paper, publicly criticised the company for firing Gebru and undermining the credibility of her work.

The pair for about two years had co-led the ethical AI team, started by Mitchell.

Google AI research director Zoubin Ghahramani and a company lawyer informed Mitchell’s team of her firing on Friday in a meeting called at short notice, according to a person familiar with the matter.

The person said little explanation was given for the dismissal. Google declined to comment.

The company said Mitchell’s firing followed disciplinary recommendations by investigators and a review committee.

It said her violations “included the exfiltration of confidential business-sensitive documents and private data of other employees”. The investigation began Jan. 19.

Google employee Alex Hanna said on Twitter the company was running a “smear campaign” against Mitchell and Gebru, with whom she worked closely. Google declined to comment on Hanna’s remarks.

Google has recruited top scientists with promises of research freedom, but the limits are tested as researchers increasingly write about the negative effects of technology and offer unflattering perspectives on their employer’s products.

Reuters reported exclusively in December that Google introduced a new “sensitive topics” review last year to ensure that papers on topics such as the oil industry and content recommendation systems would not get the company into legal or regulatory trouble. Mitchell publicly expressed concern that the policy could lead to censorship.

Google reiterated to researchers in a memo and meeting on Friday that it was working to improve pre-publication review of papers.

It also announced new policies on Friday to handle sensitive departures and evaluate executives based on team diversity and inclusion.

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UNESCOs Member States have announced there has been ‘major progress’ in the development of a global normative instrument for the ethics of artificial intelligence (AI).

In November 2019, the United Nations secretary-general Antonio Guterres congratulated the organisation for taking up this challenge, declaring that AI is a critical frontier issue for the whole UN system and the whole world.

In March this year, UNESCO asked 24 experts with multidisciplinary experience in the ethics of artificial intelligence to develop a draft recommendation on the ethics of AI.

UNESCO then launched a wide process of consultations to obtain the many points of view of stakeholders.

This involved experts from 155 countries, members of the public (through a global online survey), United Nations agencies, major stakeholders from the sector such as Google, Facebook and Microsoft, and the world of academe with the University of Stanford and the Chinese Academy of Sciences.

The resulting draft recommendation was submitted last week to UNESCOs 193 Member States. Negotiations will take place ahead of its planned final adoption by Member States at the organisation’s General Conference in November 2021.

According to a statement, the draft recommendation submitted to the international community establishes a number of overarching concepts. This includes the following.

Proportionality: AI technologies must not exceed what is necessary to achieve legitimate aims or objectives, and should be appropriate to the context.

Human oversight and determination: humans are ethically and legally responsible for all stages in the life-cycle of AI systems.

Stewardship of the environment and peace: throughout their lifecycle, AI systems must contribute to the peaceful interconnectedness of all living creatures with each other and respect the natural environment, notably with regard to the extraction of raw materials.

Gender-inclusion: AI technologies must not reproduce the gender inequalities found in the real world, notably with regard to salaries, representation, access, and stereotyping. Political actions, including measures of positive discrimination, are required to avoid these major pitfalls.

UNESCO states the organisation will assist governments and civil society players (corporations, members of the public, etc) in developing concrete awareness-raising campaigns and ethical impact assessment tools for AI in all fields.

In addition to establishing international consensus on the subject, UNESCOs experts urge Member States and AI players further to raise public awareness and stress that is important for everyone to be made aware of their digital rights.

UNESCO director-general Audrey Azoulay says, “We must make sure artificial intelligence is developed for us and not against us.

“We need a robust base of ethical principles to ensure artificial intelligence serves the common good. We have made this process be as inclusive as possible since the stakes involved as universal, she explained.”

In recent years and since the outbreak of COVID-19, there have been ever more applications drawing on AI, notably with the aim of accelerating research into vaccines and improving tracing of the virus, UNESCO states.

AI has contributed to the development of telemedicine and distance learning. It has also been used to operate drones for the delivery of medical supplies and the need for a global regulatory instrument has grown on a par with the spread of AI applications.

According to UNESCO, the potential of artificial intelligence, as described in both scientific publications and works of fiction, results in fear that machines will take decisions out of human hands, that it will erode individuals right to and that it will expose people to manipulation to the detriment of their rights.

The quantity of data collected and processed daily raises concerns over confidentiality, privacy, and the reproduction of discriminatory practices and stereotypes. Hence the motivation to create a strong foundation of ethics.

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Transparency and integrity are two key principles headlining the list of artificial intelligence (AI) ethics released by the Office of the Director of National Intelligence (ODNI). This list, released in combination with an AI ethics framework for the community, represents the first strike by the ODNI to apply guidance to the development and use of AI in the intelligence community.

The Principles of Artificial Intelligence Ethics for the Intelligence Community is brief and lists six core principles. In addition to respecting the law and acting with integrity while being transparent and accountable, AI use is to be objective and equitable; secure and resistant; informed by science and technology; and have human-centered development and use. These principles will guide AI use and development activities with the private sector, the public, the legal system and the intelligence community at large, according to the publication.

These principles buttress the Artificial Intelligence Ethics Framework for the Intelligence Community, which aims to “prevent unethical outcomes,” according to the framework. The framework is a self-described “living document,” and it calls for periodical reviews of how AI is being used to avoid “any undesired biases or unintended outcomes.”

One noteworthy aspect of the framework is that it poses many of the challenges to be addressed as questions. These would be answered by those procuring, incorporating and managing AI, and their answers would promote ethical design of AI in intelligence, states the framework.

The framework breaks down its questions into 10 query areas. “Mitigating Undesired Bias and Ensuring Objectivity” is the area that receives the greatest focus, with three paragraphs defining its importance and six questions for AI implementers. Other areas focus on understanding goals and risks; legal obligations and policy considerations governing AI data; human judgment and accountability; AI testing; accounting for AI builds, versions and evolution; documentation of purpose, parameters, limitations and design outcomes; and transparency, to include explainability and interpretability.

One area that offers little text but plays a significant role in virtually every aspect of intelligence AI is stewardship and accountability, particularly for training data, algorithms, models, output of models and documentation. The framework declares that, before AI is deployed, it must be clear who will have the responsibility for the continued maintenance, monitoring, updating and decommissioning of the AI. Questions posed largely break down this issue into more specific areas, including who is accountable for the ethical considerations during all stages of the AI lifecycle. This area also asks who will be responsible for addressing concerns that AI no longer meets this ethical framework, and which actions that person could, or will, undertake to remedy the shortcoming. These actions could range from modifying or limiting the use of AI or even stopping it completely, the framework offers.

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Richard Pilling considers the ethical responsibilities of delivering Machine Learning solutions and suggests that the immense possibilities opened up by ML should always be tempered with an understanding of potential consequences.

I was lucky to grow up in the 80s as the youngest of three children – a happy time of riding around on my Raleigh Grifter, watching Knight Rider, and playing on my Commodore 64. My

mum had a totemic and often repeated phrase of “just because you can, doesn’t mean you should” – which has always stuck with me; it was part of my mum teaching me right from wrong. It’s no surprise she went on to have a career as a social worker; helping disadvantaged children find safety, peace of mind, and good families. She instilled in them the same strong ethics as she taught me. At that time my dad was the head of Quality Assurance for a multinational, had helped invent Astroturf, and went on to write what would become ISO 9001. In essence, my upbringing was heavily influenced by a strong sense of ethics and a deep understanding of the value of innovation, and quality.

The Machine Learning revolution

We’re on the cusp of a worldwide revolution in Machine Learning – a wonderful set of tools and technologies, which have huge potential to either make the world a better place or further divide it. There’s always an ethical side to any new and potentially market-changing technology. However, unlike previous industrial revolutions, machine learning is focused on the ‘why’ of things, rather than the ‘how’ – or to phrase it another way: for the first time we’re inventing a better thinker, rather than a better ‘do-er’.

Companies have the ability to make systems that will fundamentally transform billions of lives,  all at the click of a button. Consider areas such as lack of transparency in decision making, unconscious bias, the law of unintended consequences – all to rain down upon millions and millions of unsuspecting people – the impact on society is, and will increasingly be huge.

Decisions framed as unbiased and data-based are still decisions based on what the machines have been taught from humans. We are responsible for determining what defines a “good” outcome, although it may not be a universally positive result. It’s more likely that these decisions are only useful in certain contexts and not others.

The machine, or its algorithms, does not have a sense of right or wrong as naturally have. We have a moral sense, that machines cannot learn (at least for the foreseeable future), as it’s making all decisions on data and acts as it’s told to do. It’s crucial to understand how these systems make decisions, to know why they’re being made.

There are some types of machine learning or certain algorithm classes that are more transparent than others. Some people are specifically making algorithms that are designed to be transparent so you can follow and expand on the thought process. A system that recommends, not makes, decisions and is able to explain them will be of great help across many industries.

I want to make sure that we’re not being too negative about machine learning. It is a really useful set of tools and technologies. It’s just, at the end of the day the fool with a tool is still a fool, just quicker.

Machine learning can build a bright future for us – but I’d like any singularity which may happen to be an inclusive benevolent one, rather than a nightmarish world of an all-knowing BigBrother. If you’re running at the pace of innovation, and it’s making you run as fast as you can, you need to stop and check that you do the right thing.

The time to think about this is now, before the cat is fully out of the bag.

Tech companies need to deeply consider the effects of their work – their role is to advise and help companies on the use of innovative technologies and make sure they don’t fall down a rabbit hole or ride too far on the hype-train. It’s a moral imperative to look at the ethical side of any technology, as well as its potential business value. The impact of machine learning is a topic that garners much attention, and this conversation mirrors the tenets of my upbringing: innovation, quality, ethics.

I have the good fortune to, at times, mentor bright-eyed newcomers to the world of big data and ML. I advise them to envisage the future ramifications of their work, and I often think to myself, just because you can, doesn’t mean you should!

Some things are best left to human beings…

I’d like my children to have as free and as happy a childhood as I did, discovering things rather than having an algorithm recommend them – as that can lead to an echo chamber. In this case, we should remember that some things are best left to humans. When growing up, my sisters gave me a love of music – especially 70’s disco and 80’s new-romantics. While I’m sure a streaming service algorithm could have led me that way eventually – I’m certain that the music wouldn’t mean anywhere near as much to me!

There are clearly thousands of use cases where ML can help optimise our experiences. However, let’s not forget the need for a ‘human’ element to enrich those experiences.

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The economist David Ricardo, when he had in 1821 written about the impact of machines, could not have imagined their pervasive influence on our lives. Today, robots controlled by supercomputers, self-driven cars, board games that are programmed to outsmart humans, complex algorithms that replicate the human brain, and neural networks – have become ubiquitous. AI helps, for instance, to triangulate and analyze data from radio-collared endangered animals and their ingrained behavioural patterns – if a natural predator comes near a deer they scatter, but if a man with a gun comes they all move in opposite directions. 

As more and more data is captured and as data processing becomes more ubiquitous, the implications of AI are not just to jobs and workers, but to all of society and our very existence. Are we sure we are not creating a Frankenstein like entity that will imperil its own creator? Like HAL 9000 in Arthur C Clarke’s 2001 a Space Odyssey, a potential rogue that attempted to destroy its creators?

In the race to lead in AI, Canada has created the Canadian Institute for Advanced Research and the Neural Computation and Adaption Group, largely by allowing for openness in approach. Top companies like Facebook and Samsung have opened AI development centres in Canada. China is surpassing even the US in AI research today and it has 700 million smartphones. With a massive number of people using digital payment systems, a large volume of data is being generated and that is being consumed and analyzed effectively by firms such as Baidu, Tencent etc for higher AI proficiency in fields such as messaging BOTs and facial recognition. 

While India must prepare to ramp up its act on the AI front, we should be careful about AI applications in sensitive areas like for instance the justice delivery system – it is important that the data that is used for analysis does not have latent biases. In the US, for instance, it was found that AI determined criminal justice caused Africa Americans to be targeted because the system had been trained on historical data that had them as the subject of historical prejudices. In America, the technology giants of Silicon Valley have pledged to work together to make sure that any AI tools they develop are safe. All the leading AI researchers in the West are signatories to an open letter from 2015 calling for a ban on the creation of autonomous weapons. But that should not make us complacent.

Unlike conventional technology, the depth and effectiveness of AI is hard to fathom. In areas of health, autonomous vehicles and defence it can make a difference between life and death – the attack on the Aramco plant and the killing of the Iranian military commander in Iraq are examples of the sharpness that AI can bring into military operations. But, we must also factor in quirky possibilities with fatal implications. What happens if an AI system goes berserk and triggers a reactive missile attack on the basis of its own disintermediated and perhaps miscalculated assessment of a preemptive attack from the enemy? India should take the lead in raising the subject of ethics, safety and transparent standards that cannot be manipulated in the use of AI. At the same time, it must work strategically towards raising its own AI competencies in a coherent and rational manner.

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Artificial intelligence is everywhere. It is in your phone. It is in almost every app on your phone. It powers the software in your computer and tablet. These intelligent algorithms even recommend the next TV show or movies you should watch on Netflix. It is therefore not surprising that the Government of India is looking to regulate artificial intelligence (AI), with a clear set of guidelines for how the AI technology is developed and implemented. This has been confirmed by Suresh Prabhu, Minister of Commerce & Industry and Civil Aviation in the Government of India.

“Ideas and #Technologies have a broader impact in today’s society and it must be governed and guided by ethics for a better tomorrow, Prabhu said in a tweet, announcing the Narendra Modi government’s stance on the emerging artificial intelligence based technologies and the need for regulation. This comes at a time when there is already a debate on data privacy and data security in the online space, particularly with regards to how social networks such as Facebook and Twitter safeguard user data. This also follows the announcement by standing Finance Minister Piyush Goyal in the Budget 2019 announced earlier this month, that the government of India was considering a national centre for artificial intelligence, and will also be unveiling a national AI portal soon.

It is perhaps the increasing reliance on the use of machines, machine learning and the use of smart algorithms to power artificially intelligence systems, which makes it prudent for regulation. The fear that has always existed with AI and the algorithms that power it is how it comes to making a certain decision based on the data that is available to it at that point of time, and how to ensure that it makes the correct decision every time. This is where the question of the ethics of AI comes into the picture, which the government expects to tackle with some amount of regulation.

Then there is the whole question of who owns the data about the users, and how that data is used to further power AI based apps, services and platforms. As things stand, a larger chunk of the data that is collected by AI, and further used to improve AI, is still controlled by certain companies. The government wants to put in place some mechanisms and policies about how these algorithms are written and how the data is collected in the entire process is used, safeguarded and perhaps even further tracked.
India will be following the lead of countries such as Canada, Singapore, France, China and the UK, to name a few, to formulate and eventually implement policies and regulations that control the use of AI.

For instance, in the 2018–2019 budget, the government of Australia announced a four-year plan and set aside AU$29.9 million to support the development of AI in Australia. At the same time, they will create a Technology Roadmap, a Standards Framework, and a national AI Ethics Framework to support the responsible development of AI.

In July 2017, China had unveiled what is called ‘A Next Generation Artificial Intelligence Development Plan’, which sets a roadmap for as far as the year 2030 with regards to the development of AI in China and also the regulations and ethics to promote the development of AI.

In April 2018, the European Union outlined the Communication on Artificial Intelligence document which among other issues, outlines the need to have an ethical and legal framework is in place—and will prepare the draft guidelines which member countries would most likely adopt as is, or with certain localized changes.

It is not entirely clear at the moment as to when India’s first draft for the AI policy will be ready, or what all will fall within the purview of the guidelines and regulations

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Facebook and the Technical University of Munich are joining forces on the creation of an independent ethics research center for artificial intelligence.

The social network will provide $7.5 million in funding over five years for the Institute for Ethics in Artificial Intelligence, with director of applied machine learning Joaquin Quiñonero Candela saying in a Newsroom post that the aim is to advance the growing field of ethical research on new technology and to study the fundamental issues that are specific to the use and impact of AI.

Candela called TUM one of the world’s top-ranked universities in the AI field, saying that the Institute for Ethics in Artificial Intelligence will tap into the school’s work in subjects such as robotics, machine intelligence and the social implications of AI.

He added that Germany’s creation of government-led ethical guidelines on autonomous driving and its work with European institutions on ethical frameworks for AI will also benefit the center.

Lütge said, “We will explore the ethical issues of AI and develop ethical guidelines for the responsible use of the technology in society and the economy. Our evidence-based research will address issues that lie at the interface of technology and human values. Core questions arise around trust, privacy, fairness or inclusion—for example, when people leave data traces on the internet or receive certain information by way of algorithms. We will also deal with transparency and accountability—for example, in medical treatment scenarios, or with rights and autonomy in human decision-making in situations of human-AI interaction.”

Candela said Facebook may also share insights, tools and industry expertise on topics such as algorithmic bias, adding that the Institute for Ethics in Artificial Intelligence will explore funding opportunities from entities other than Facebook, and it will seek to publish research, work with other experts, organize events (conferences, symposia and workshops) and create educational activities with other institutions.

He concluded, “Realizing AI’s huge potential for good while balancing its risks is a global effort, and it will not be accomplished overnight. The Institute is an exciting step forward in our continued commitment to partnering with academic institutions, governments, NGOs (nongovernmental organizations), advocacy and industry groups, and others who are working to advance AI in a safe and responsible way.”

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