Ubiquitous artificial intelligence
When it comes to the concept of artificial intelligence, you may think it is an obscure and incomprehensible field. Still, one sentence will give you a general idea: “Artificial intelligence” is what humans give to machines. The mainstream approach to AI is machine learning, which means that machines learn like babies, simulating and implementing human learning behaviors to acquire new knowledge and skills.
At present, the application of artificial intelligence has penetrated every aspect of our lives. Next, I will show my friends the artificial intelligence around us with the help of typical artificial intelligence applications in our lives:
1) Apple’s Siri, Xiaomi’s Xiaoai, Microsoft’s Bing, and other intelligent assistants
Pick up our phones and talk to Siri, Xiao Ai, etc. You will find that they can chat with you like a friend, “What’s your name?”, “Are you happy today?”……
Try chatting with the AI voice assistants; they might make you laugh.
In addition to this, they can search for information for you:
If you suddenly can’t remember how to spell a word, try asking Siri! And you might ask Siri what “artificial intelligence” means, or if you want to check your calendar, find a nearby mall, pharmacy, library, etc., ask them. They can turn your phone into a clever little secretary.
Smart stereos are similar, such as Apple’s HomePod, which can talk to you freely, ask it for the weather, or ask it to remind you that the dumplings are ready in 7 minutes. If you have one at home, try talking to your AI!
2) Driverless cars
Have you ever seen a driverless car? As the name suggests, a car starts, drives, and stops without a driver.
A driverless car is an intelligent vehicle called a wheeled mobile robot. It relies primarily on a computer-based intelligent driving controller in the vehicle to achieve driverless-ness. The technology involved in driverless cars contains several aspects, such as computer vision and automatic control technology.
Once we thought of self-driving cars, planes and spaceships as elements of science fiction, but now these elements are about to become a real reality though the AI.
Robots are also an application of artificial intelligence. We have been using robots in industrial manufacturing for a long time. For example, Foxconn’s mobile phone production lines, Walmart’s warehousing centers, and Jingdong’s logistics sorting all use robots to replace humans in repetitive and tedious tasks.
（Source from: https://flic.kr/p/FwZuk7)
4) AI art
Artificial intelligence can also create art. Have you ever used Prisma, an app that can transform a photo into a painting?
This process can be seen as a child’s creative training with a photo, which can be used to create a variety of oil, watercolor, and cartoon techniques by copying classic Chinese and Western paintings.
This development of technology allows ordinary people to “create art.”
5) Face Recognition
Face recognition, also known as portrait and facial Recognition, is a biometric technology that identifies people based on their facial features. The technologies involved in face recognition mainly include computer vision, image processing, and so on.
Face recognition technology has been widely used in many fields, such as finance, justice, public security, border control, aerospace, electric power, education, medical treatment, etc.
To give you an interesting example: the “fugitive nemesis” – Chinese singer Jacky Cheung.
On 7 April 2018, a fan in the stands was taken away from the venue by the police right after Jacky Cheung’s concert in Nanchang started. Security personnel locked him in the frames through the face recognition system.
On 20 May 2018, at the Jacky Cheung concert in Jiaxing, the suspect Yu was identified as a fugitive by the face recognition system when he passed through the security gate and was subsequently arrested by the police.
One fugitive was arrested at the 2018 concert in Jiangmen, Guangdong.
18 fugitives were arrested at the 2018 Hainan Haikou concert, among others.
It is said that more than 60 fugitives have been captured for attending his concerts so far, so netizens have dubbed Jacky Cheung as the “fugitive’s nemesis.”
By the way, facial Recognition is one of the ways we use our faces to unlock our smartphones in our daily lives.
In addition, AI is involved in many aspects of our daily lives. TikTok uses big data to recommend videos we like to watch; we can compose photos or videos through AI. There are even virtual idols, virtual news anchors, etc.
The ethical challenges posed by artificial intelligence
(Source from :Baidu)
As technology becomes widely used, although it brings opportunities and emerging markets, remember the risks that come with it. These include but are not limited to information cocooning, Filter Bubbles, Echo Chamber effect, data privacy, algorithmic transparency and information symmetry, discrimination and bias, and Deepfake.
Our technological tools are not yet mature, the relevant ethical regulations are still missing, the public is not yet sufficiently literate, and the supervisory and management system is imperfect. All of the above need to catch up, which is out of sync and inconsistent with the rapid development of AI and the impact it will have on human society.
1) Driverless car ethics
On the evening of 18 March 2018, in Tempe, Arizona (USA), a pedestrian named Elaine Herzberg was struck by a self-driving car that was testing and tragically died from her injuries. The vehicle involved in the accident had a driver inside at the time. Still, the car was controlled by a fully self-driving system (artificial intelligence). The incident became the world’s first case of a self-driving car hitting and killing someone. The aftermath has sparked public thinking worldwide about ethical, moral, and legal issues in artificial intelligence.
The question that has been repeatedly raised is: who is responsible for this unfortunate incident —— the company’s testing department that owns the self-driving car, the designer of the AI system, or even the manufacturer of the onboard sensing equipment?
2) Robot ethics
In 2017 Sophia became the first robot to be granted citizenship in Saudi Arabia. The question arises: does she have the same legal status and citizenship as a human? If Sophia breaks the law in the future, will the designer, the maker, or Sophia herself be punished?
3) Algorithmic ethics
Challenging the traditional standards of news value judgment
Judgment of news value is the core of media practitioners to achieve professional autonomy. The application of artificial intelligence in news communication practice has already acted on the judgment of news value. It has derived a set of judgment standards different from traditional news value — “algorithmic value. “Some scholars believe that, to some extent, the algorithmic value may replace traditional news value.
Judging from the current situation, AI is a tendency for the criteria for judging news value to become traffic. The living space for in-depth reporting and quality content is constantly squeezed. On the one hand, fake news and reverse news are frequent. On the other hand, entertainment and homogenized content are increasing, and people are beginning to favor exaggerated news headlines.
The problem of the public nature of news
Reporting information, providing a platform, and monitoring power are the three missions of the news media. Hence, the news has public nature, and its fundamental value lies in public service. However, under the domination of algorithms, the issue of the general nature of communication is particularly urgent. The current situation and direction are worrying, such as information control being in the hands of a few technology giants.
The development of digital platforms has given rise to a series of new monopolistic practices characteristic of the digital economy. These monopolistic practices take advantage of technology, data, and algorithms with apparent network effects, posing an increasingly serious threat to the order of market competition.
Influence on public opinion and user autonomy
The role of the “reviewer” in the traditional news dissemination process has been replaced by artificial intelligence to a certain extent, and the review function has been weakened. The logic of filtering, selecting, and pushing information in algorithmic news recommendations is an “algorithmic black box” for users, which most people cannot decipher.
Recommendation algorithms can cause users to lose control of what they read. This is because the recommendation algorithm calculates the similarity between news and users, and between users and users, to make recommendations for news/content, which somehow results in users not being able to fully express and decide their own reading interests, therefore not being able to choose what they want to read.
The “echo chamber” effect radicalizes users’ perceptions. There are three well-known concepts in critical algorithmic recommendation research: the “information cocoon” emphasizes the risk of being trapped in a “cocoon” by actively selecting personalized information. “The ‘filter bubble’ emphasizes the filtering effect of interpersonal relationships in social media and algorithmic recommendation functions. The “echo chamber” refers to the fact that users have already pre-determined a particular position before receiving information and thus tend to gravitate towards similar details and views, which can lead to the formation of inter-group identification and cognitive solidification within a specific group of Internet users.
How to govern the ethical issues of AI?
Micro level: media communication field
1.Play the leading role of journalists and collaborate symbiotically with intelligent technologies
Journalists can strengthen their expertise in innovative technology and actively and rationally harness it for journalism. In this process, they should review the authenticity and rationality of information data processing and algorithm recommendations and carry out a scientific division of labor and collaboration with artificial intelligence so that journalism is grasped by human editors and intelligent technology.
2.Strengthen the construction and supervision of new regulations and reshape news values
First, we should improve the laws, regulations, and regulatory mechanisms for using artificial intelligence technology. For the collection and dissemination of news data, the algorithm system’s information filtering and decision-making rules, as well as user information sovereignty, carry out the legal and policy guidance in different categories.
Secondly, intelligent news should combine the characteristics of the current intelligent media environment, correctly handle the relationship between news production and intelligent technology, news services, and commercial interests, and guide audiences to think and examine news scientifically and rationally.
3. Scientifically promote the improvement and application of intelligent technology in the media industry
In terms of algorithms, there is a need to improve transparency and accuracy of algorithms. A reliable data guarantee mechanism should be established, the technical literacy and ethical responsibility norms of intelligent technology engineers should be improved, and the algorithms’ operating rules and verification process should be appropriately disclosed.
On the data side, all aspects of the news information data collection and use process need to be handled with care. Through data source analysis and screening and filtering regulatory mechanisms, relevant misinformation can be excluded to ensure that technical data is balanced with the news content.
Macro level: social and national perspectives
1. Promote interdisciplinary and pluralistic governance of ethical research on artificial intelligence
Construct multi-disciplinary governance with the joint participation of government, market, social organizations, and academia to achieve precise control of AI; at the same time, non-government stakeholders, including individuals, teams, and institutions, are also key to developing an ethical governance system with practice. This multi-party collaborative governance should be a self-organized system with government as the core and collaborative subjects such as enterprises, research institutions, associations, and the public participating; and through building a global cooperative governance mechanism to achieve global co-intelligence.
2. Establish ethical principles and governance rules for AI that are consistent with the realities of each country
Ethics is contextual, and different political systems, cultural systems, and social ideologies in different regions have different standards for viewing the ethics of AI, which are likely to be fundamentally different according to ethnicity, religion, culture, etc. Therefore, attention needs to be paid to the social context of practice, such as the stage of national development, regional market conditions, and cultural values of a particular area.
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