AIAE » E-LEARNING » INTERVIEW 6
AI and societal challenges
The following interview snippets were given by Simon Delakorda and cover the social impact of AI with daily life examples, the societal challenges of machine learning and the roles of institutions in the field of AI regulations.
transcript
Hello everyone. My name is Simon Delakorda. I’m director at the Institute for Electronic Participation from Ljubljana, Slovenia. The Institute for Electronic Participation is a nongovernment organization which is active in the field of information society, development and digitalization. We are also relating dealing with the issues of artificial intelligence. For example, last year we implemented a citizen dialogue which was also covering actual relevant issues with the development of the artificial intelligence. How this technology is relating to the everyday life of the citizens.
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The Interviewee, Simon Delakorda, is the director of the Institute for Electronic Participation in Ljubljana, which is a non-profit organisation that deals with
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transcript
So starting with my first question what is artificial intelligence and how it relates to society? Usually artificial intelligence is described as a technique that enables computational system to mimic any type of intelligence. Maybe this is sounds a little bit technical but basically it means that a machine is capable of solving a specific problem. So some refer to artificial intelligence as a technical approach, others define it as the combination of software, hardware and data. But in any case, artificial intelligence compromises various tools and methods. For this reason is also very hard to identify the artificial intelligence. So at the moment we have these broadly accepted definitions because frankly speaking we still don’t know even what actually human intelligence is and how to properly define it. So you can imagine that we also have this problem with the artificial intelligence. But to go to the straight to our experience without artificial intelligence applications everyday lives we can see already today that there is many number of different applications which are offering huge support and also help to make our life easier. For example, most typical examples of usage of artificial intelligence in society are for example speech recognition. Many of you are probably familiar with the theory by Apple or Alexa by Amazon which includes intelligent systems and they’re actually artificial intelligence systems to recognize speech inputs and based on this speech inputs those systems then delivering different services or comments to implement different tasks. So the next such example of using artificial intelligence in society which is quite common today is personalisation. For example when we are browsing online social media platforms or online services or for example Netflix or Amazon, those web services are using artificial intelligence systems in background which is personalizing the content and presenting this content to our web browsing habits or needs. For example if we are using if you’re searching for particular content or a product then based on your history or behaviour of searching these applications then give you the search matching for the content that you are most likely which is fitting your interest and it’s recommended to you. Then the third such example of using artificial intelligence is everyday life which is also very useful for me is for example email filtering. We all know that there is many spam emails coming into our main mailing box and we can use artificial intelligence programs that can distinguish between the real email and the relevant emails and spam emails in your email folders. And also for example one often artificial intelligence application which is used today is also in healthcare, for example clinical diagnostic. In medicine artificial intelligence is more and more used to support the work of doctors in their diagnosis. But what we are talking about in these cases is that we are talking about a narrow artificial intelligence because these are the cases which are able to solve very well defined and somehow narrowed problems, practical problems. But we also when we talk about artificial intelligence. We can also speak in this general artificial intelligence which refers to the system that can perform any intelligent tasks that human will be able to perform. Of course, this is still not a reality. There are some predictions for the future that maybe also artificial intelligence will be able to solve more complex and more bigger tasks that are now at the moment related only to the human type of the intelligence. So to conclude this initial introduction about the artificial intelligence in society, we can see that there are many applications of artificial intelligence. Some of them are incredibly positive, having impact on individual society and individuals and society and are also bringing great opportunities. However, we also have to be aware that artificial intelligence can also discriminate and they can disadvantage certain group of people. That’s why for this reason it’s very important that we understand the relationship between the artificial intelligence and society, especially in terms of accountability, biased transparency, data quality and other ethical problems arising from using artificial intelligence.
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1) What can a machine with AI do?
2) Do we know the exact definition of AI?
3) What type of results do we get with the help of AI when using a browser?
4) What does AI do with relevant and spam emails in online mail services?
5) What types of problems does narrow AI solve?
6) What type of task can a general AI perform?
7) Could AI in the future solve more complex problems than a human can?
8) What can be the negative consequence of AI in society?
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transcript
So now the next view or issue relating to the artificial intelligence I would like to focus on is the social challenges of the machine learning. First of all, what is machine learning? Machine learning refers to algorithms and techniques that learn from by themselves, who are confronted with data, observations and interactions with the surrounding world. Basically, machine learning is about algorithms. It’s based on the algorithms and algorithms are simply set instructions how to solve tasks. And now when relating algorithms to the machine learning means that a particular type of algorithm can be learned, but not by the human programmers, but by themselves. Meaning that machine learning is learning by themselves by using statistical approach. And usually there are two phases of machine learning. The first phase is that the machine learning algorithms are being trained by using data, by using the training process. And the result of this process is machine learning model. And in the second phase, this machine learning model is applied to the desired area of application. The idea is that this machine learning model is then solving a problem that we would like to address. For example, machine learning models for prediction if a patient has cancer, tumour or machine learning model, or for prediction how the stock markets is going to behave in the future. Of course, there are some issues issues with machine learning because machine learning can have a serious impact on people’s lives and especially when there can be errors in machine learning which can happen during data collection, data preparation or during the training process. And also we can have issues when we misinterpret the results of the machine learning process. Looking at the social level, a great danger is that the training data used for the training process for machine learning is considered perfect. But we know that perfect data sets would require all possible factors that constitute or influence the situation that we are addressing. To mean that it’s very hard to train algorithm, that they are using all the data from the complex society. And as a result of this imperfect data which is then applied to the machine learning algorithm, it can happen that the results can be too simplified and a situation they are addressing only has a limited number of factors taken into account. The results of this is that the machine learning can lead to bias prediction, especially for the disadvantaged groups of society which are not so much present in data or in the society as a whole and are less represented in the data set. For the case of the bias in the machine learning, this means that the bias data will also result in biased prediction. This is for case when it comes to the rare phenomena or social contexts that are hard to quantify. This means that we really have to be very aware of those specifics with the society which are not seen or included into the machine learning results. Because machine learning is actually operating based on the patterns. And if those patterns are lacking occurrences or being of poor quality, we can get very biased and poor results.
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True or false?
Unlike human operation, there are no errors in machine learning.
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True or false?
In machine learning a mistake can be made during data collection and preparation.
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True or false?
There can be no misinterpretation of results in machine learning.
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True or false?
It’s very hard to train an algorithm which uses a huge amount of data from society.
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True or false?
One of the problems with machine learning is the oversimplification of results..
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True or false?
With machine learning we avoid discriminating a part of the population that is not often included in databases.
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True or false?
Biased results are the consequence of truncated patterns in society.
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transcript
So now how to avoid or how to address those biases, those ethical issues with machine learning and artificial intelligence on the international level, but also on the level of the national countries, national states. There is huge debate going on how to establish a system which would govern, which would regulate the usage of the artificial intelligence in society and of course for the impact which is having this technology for the society. And the main question here are who is responsible if something happens with the artificial intelligence? Something goes wrong if there are errors. So who’s responsible, accountable for the results of the artificial intelligence use, how to deal when there is an accident, if there is a wrong diagnostic or if someone is being disconnected because of the artificial intelligence. The UNESCO, this is the United Nation Agency is working very actively on policy proposal how to frame the governing of the artificial intelligence. And they provided a set of policy proposals and policy proposals which are dealing with different aspects of the governing the artificial agents. Now I will briefly present those aspects which I think are very important and also can be used as guidelines for understanding what to be a society and as individuals have to be aware when thinking about the artificial intelligence impact on the society. First of all, the first aspect which is important is that the artificial intelligence is promoting diversity and inclusiveness. Meaning that the artificial intelligence have to function in terms to combat of culture and social tester types. And inequalities this is important to these biases when machine learning patterns, in case that they are based on the poor data, they can often discriminate and they can also enforce the resisting stereotypes. This is for example with this facial recognition artificial systems which are already scientifically proven that they are more often biased towards the colourful faces than to the white faces. Then the second important aspect is the impact of the artificial intelligence on the economy, on the employment. There are different interpretations how the artificial intelligence applications will contribute to losing particular jobs. Many there going to be some jobs that are not going to be necessary anymore and this is going to have an impact on the different working groups. And artificial intelligence, especially high driven economy should take into account upskilling and reskilling measures that will enable workers or employees who are going to be affected by the negatively by artificial intelligence that they still remain a part of the labor market. Then the third important thing is addressing social and economic impact of AI. Meaning that artificial intelligence shouldn’t generate monopolies in terms of research, knowledge, data or the market, that not some specific stakeholders or countries or regions are going to benefit from this technology, but the humankind as a whole. Also then a logical view is also impact on culture and on the environment. Meaning that the artificial intelligence is not having a negative effect on the culture, diversity, development heritage and also on the environment. And then is a set of four or five views which are actually all dealing with the artificial Intelligence ethics. The Artificial Intelligence Ethic is very important in terms of creating a value based background on which we developed the Artificial Intelligence. And there are those aspects of ethics which relating to the education and awareness, meaning that artificial intelligence should be teaching in schools and universities so that the students and schoolers can get familiar with the artificial intelligence technology. And what is this relationship between the technological and social domains. And also very important is the view on the ethics of the artificial intelligence research, meaning that there is research, especially in the private sector, which is being funded by the private money that is taking into account the social responsibility. Also the benefits of the research in terms of the humankind, not only the market and for profit interest, then it’s also an important aspect of ethical use, AI. In development, meaning that the artificial development should strive to provide platforms that allow international cooperation on AI development. Meaning that not the AI development is just for the rich countries, but also that those developments are also applied in the poorer countries which are not so rich. And from this very important aspect is that we create a kind of international cooperation on the Artificial Intelligence ethics. For example, UNESCO forum is a very good example of this, when different countries with different stakeholders are discussing about the artificial Intelligence future and how to govern it in terms of ethics and value for the development of the society. And from this it is very important that there is also a kind of government mechanism which oversees the development of the artificial Intelligence on the global level in terms of inclusiveness, transparency, check and balancing. These are very important and also multilateral cooperation. These government mechanisms are referring to the digital ecosystem for the artificial Intelligence, which includes infrastructure, digital technologies, knowledge sharing options and especially cooperation with different stakeholders that they have voice and they can share their considerations and concerns how to develop Artificial Intelligence for the future.
Quiz question 1/8
Is the establishment of principles to regulate the use of AI one of the proposed solutions to avoid the possible negative consequences of AI?
Is it true that in the case of an AI error, the main problem is defining who is responsible for it?
Is UNESCO responsible for governing artificial intelligence?
Would the integration of the principles of diversity and inclusiveness in AI, further increase discrimination and inequality within society?
By following UNESCO’s proposal for diversity and inclusiveness in AI, do we avoid mistakes caused by poor data?
Does the UNESCO’s principle of economics mainly refer to employment issues as a consequence of AI?
Can AI have a negative impact on culture, diversity, development, heritage and the environment?
Should the concepts of AI be taught in schools and universities in order to raise awareness of the relationship between AI and society?
Do international cooperation platforms bring the possibility of AI development closer to poorer countries?
Could governance mechanisms regulate the development of AI, meaning inclusiveness, transparency, multilateral cooperation at the global level?
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transcript
So and my last view on the artificial intelligence is relating to that I would like to share today’s relating to the role of the civil society organizations, especially the role of non-governmental organizations. I think that the role of non-government mentalization in the application of artificial intelligence is very important from the viewpoint of explaining citizens, explaining people, users, everyday people how this technology is affecting their lives, especially in terms of trust into the artificial intelligence. Also in terms of helping them to understand the applications and the impact of the everyday life of the citizens, because there are different interpretations and fears and maybe unfounded negative, their relationship towards the artificial intelligences, which are needed to be discussed, learned educated in trustworthy environments and non-governmental organizations with their members, with their voluntary activities are a link often between the high tech research and everyday people because they are having trust because people having trust in non-governmental organizations. And because of their information, their education activities, and can help citizens to understand what the negative and positive effects of artificial intelligence are. This is one role of the NGOs. And the second role of the NGOs is that they act as watch dogs. That they act as a not exactly supervising body, but someone who is paying attention to the possible discrimination, breach of human rights or negative usage of the artificial intelligence, which can lead to discrimination, which can lead to worse conditions, for immigrant groups, for specific social groups like immigrants or women or Socially vulnerable groups which are not as represented in the society as other social groups. And the NGOs must take the role of safeguarding their rights and also battle combat for human rights when they see that the artificial intelligence is about to bridge those standards. I think these are two main rules of the NGOs relating to the artificial intelligence. There are two minor roles. One is also NGOs as a usual user artificial intelligence, especially those NGOs who are generating large data on this society, and then can then use this machine learning, tools to provide some conclusions, to solve problems, to create visualization on different aspects of society. And the second this role is also important is that the stakeholders are acting as a policy actor, meaning that they are taking part in the forums, coalitions, discussions with other stakeholders on the economy, from the politics, from the research. And so that and those forums, those discussions, they are pointing out the issues of accountability, responsibility, privacy, trustworthiness of the artificial system, basically, meaning that they work as advocates of the society and the humans and strive for the human oriented use of the artificial intelligence. So this would be my, short but not really short viewpoints on the artificial intelligence and the society.
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Why are non-governmental organisations (NGO) important for AI?
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In the case of AI what are non-governmental organisations (NGO) paying attention to?
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How do non-governmental organisations (NGO) use AI?
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In what way do non-governmental organisations (NGOs) act as policy actors?
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