© REUTERS/Stringer

In its quest for technological supremacy, China has a specific soft spot: its chip industry.

Beijing semiconductor efforts in the recent years and decades have not born fruit. Be it microprocessors, memory chips or mobile processors, in all of these fields the country is still not capable of developing its own top-notch assets on a large scale. Consequently, there is still a high reliance on chips produced by the semiconductor market leaders, normally situated in the US (e.g. Intel) as well as in Taiwan (e.g. Taiwan Semiconductor Manufacturing Co, or TSMC) and South Korea (Samsung Electronics).

This high level of dependence became very clear recently: In 2018, after the Chinese smartphone manufacturer ZTE was accused of illegally selling US equipment to Iran and North Korea, the US Department of Commerce imposed a ban on American companies selling their products to the company. Unable to buy chips from American chip makers like Qualcomm, ZTE teetered close to bankruptcy.  From a Chinese perspective, the last straw came when the same procedure was used in May, this time with telecoms giant Huawei as target.

These actions served as a wake-up call for China, pushing it to put greater efforts into achieving technological self-sufficiency—a claim already made by President Xi Jinping. This blatant exposure of China’s vulnerabilities in the global supply chain feels particularly painful for decision-makers in Beijing since Chinese strategists themselves pursue precisely this approach—pushing others to become technologically reliant on China and weaponizing this “interdependence” to exert economic and political pressure when required.

Untapped Market Potential

To reduce its reliance on foreign semiconductor industries, China has set up initiatives and funds to counteract the trend. However, according to Gu Wenjun, chief analyst at Shanghai-based semiconductor research company ICWise, it will take up to 40 years for China to reach self-sufficiency in many areas of chip production.

Although China has most probably lost the battle on “traditional chips” for the time being, it might win another one: In line with its ambitious and aggressive efforts to become an AI superpower, Beijing has recently started to cast an eye on AI chips. These chips are specifically designed to process and compute machine learning algorithms at a faster pace and are optimized for AI-specific functions, be it in the context of autonomous vehicles or robots as well as within the framework of cloud computing services or data centers.

For instance, this September, Chinese tech giant Alibaba officially entered the AI chip market by presenting the Hanguang 800. According to the company, this AI chip can shorten computing tasks that would usually last one hour down to a couple of minutes. Just one month earlier, Huawei presented its first commercial Ascend 910 AI computing chip. Other tech companies and start-ups such as Baidu, Tencent, Bitmain or Horizon Robotics intend following suit to capitalize on a niche in the semiconductor industry that still possesses market potential on an international scale.

Even though their American counterparts such as Google and Facebook have also already entered the “AI chip race” (at least for in-house purposes), no clear leader can be perceived so far, which gives Chinese companies a chance to successfully exhaust this untapped market potential.

Role Model for Europe

At first glance, one could simply regard this as yet another field where China will take a bold step in its efforts to solidifying its position as AI superpower. However, Europe can learn from the Chinese approach when it comes to its own endeavors to catch up in the global AI power game. It can detect the areas within the AI industry (or in the technological realm in general) where there are opportunities to gain ground or even to take the lead globally by benefiting from the first mover advantage—as the US and China have done when it comes to many AI-related components, which have been missed by Europe in the past.

One such area, for instance, could be using AI systems to process machine and engine data (temperature, pressure, rotor speed, etc.), which has a strong industrial base in Europe. With such an approach, Europe could combine its strengths in the physical world (i.e. its manufacturing industries) with AI technologies, also in the context of the increasing data generated by the Internet of Things (IoT). On the other hand, heavy investments in consumer data would most probably mean fighting a losing battle with the US and China.

There are also other data types where Europe could showcase its strengths: According to a study by the Center for Data Innovation, public health data can be leveraged on a large scale within the EU and could provide an opportunity for fueling further AI developments. Another related opportunity for Europe could be to focus on the quality of data, which can compensate for the lack of quantity to some extent. China, for instance, is said to have weaknesses in compiling structured data. However, in order to build on these scenarios, private sector data-sharing approaches in the business-to-business and business-to-government areas must be further supported by institutions such as the European Commission.

Against this backdrop, the European Union and its member states still have a chance to gain ground in the global AI industry. Within this context, however, the debate concerning AI ethics for Europe as a unique selling point is important but not sufficient. In combination, however, with a related thriving industry or at least with certain strong points in the European AI ecosystem, such a human-centered digital area can be developed to its fullest potential in order to compete with the US and China.

The post What China’s “Chips Endeavor” Can Teach Europe appeared first on Berlin Policy Journal - Blog.

© REUTERS/Jason Lee

Artificial intelligence (AI) is turning into an essential enabler for economic and military affairs. It has also become the tool of choice for surveillance activities in certain countries. Against this backdrop, governments, international organizations, and corporations have been drawing up guidelines on the ethical design and usage of AI algorithms and data.

In 2018, major technology companies already drafted related principles, which is hardly surprising as AI innovations nowadays mostly originate from the private sector. Google published AI at Google: Our Principle, while Microsoft wrote Microsoft AI Principles. Yet their data-driven business model and their commercial interest in AI fuel distrust. Critics accuse them of “ethical white-washing.” The reproach is that their published guidelines are nothing more than a marketing gimmick which aim to distract from their abusive and massive application of AI algorithms.

Irrespective of whether these accusations are true or not, there is an urgent need for stakeholders other than “profit-driven players” to become genuinely engaged in the AI ethics debate. In April 2019, the European Commission released its “Ethics Guidelines for Trustworthy Artificial Intelligence.” These guidelines were drafted by the 52-member High-Level Expert Group on Artificial Intelligence (HLEG AI), which consists of representatives from politics, industry, research institutions and civil society. The document encompasses seven guiding principles, among them transparency (the traceability of AI systems should be ensured), privacy and data governance (citizens should have control over their own data) and diversity, non-discrimination and fairness (which tackles the bias problems of AI systems).

In May, the Organization for Economic Co-operation and Development (OECD) released its AI ethics guidelines, the “Recommendation of the Council on Artificial Intelligence.” Even though the document is shorter than the EU one and lighter on detail, its principles are noticeably similar. Later that month, the Beijing AI Principles were announced by the Beijing Academy of Artificial Intelligence (BAAI)—an organization backed by the Chinese Ministry of Science and Technology and the Beijing municipal government—in a joint effort with several Chinese research institutions and industrial groups involving firms like Baidu, Alibaba and Tencent. In comparison with the guidelines provided by the EU, these principles are more descriptive and less comprehensive. However, they cover three crucial clusters: research and development, use, and governance.

Promising Signals

At first sight, it is a welcome development that major international organizations and powerful states are officially looking at ethical concerns about AI. And indeed, it is possible to identify positive aspects for each of the released AI guidelines and their wider significance: the EU document has great scope and is deliberately defined as a living document to be reviewed and updated over time. Given that AI systems are subject to constant changes and need continuous adjustment, such a mechanism is indispensable. The EU also includes a checklist with easy-to-understand questions that companies can used as points of orientation to ensure that ethical concerns are respected.

With regard to the OECD recommendations, it worth noting that—even though it is a non-binding document—it is backed by the United States. This means that the Trump administration is officially voicing ethical concerns about AI at an international level, despite its skepticism toward multilateralism. In addition, these recommendations are not limited to the 36-member states of the OECD—six non-members having already also embraced these principles. As a follow-up measure, an AI Policy Observatory will be established to help implement and monitor adhesion to these principles throughout the world. Based on these recommendations but with a more limited scope, the G20 meeting in Japan this June agreed a set of G20 AI Principles. Both the US and China were signatories.

Last but not least, there the promising sign of the Beijing AI Principles. It was surprising and gratifying to see that China’s government—which is widely criticized for using AI as a tool to monitor and grade citizens—is suddenly interested in ethical concerns and that, for instance, research and development of “AI should serve humanity and conform to human values.” This can be interpreted as a signal that China wishes to become engaged in a dialogue with international partners in spite of the increasingly powerful narrative of an “AI race” with the United States.

Stumbling Blocks Ahead

Nevertheless, it would be premature to speak of a new era of AI multilateralism and an effective AI ethics framework. The recent haste in drafting AI guidelines is partly motivated by the desire not to be left out of the conversation and the “standard setting game.” It marks the start of a likely long-running debate within the international community, with many stumbling blocks ahead. A small sample of these lingering challenges follow:

First, the devil will be in the detail, as the principles presented by all sides are still very vague. Even the most comprehensive and detailed guidelines—the ones drafted by the EU—fail to set non-negotiable ethical principles or so-called “red lines.” This was even criticized by one of the members of the HLEG AI, the philosopher Thomas Metzinger. At present, all of the three principles are more about opening up new thematic areas such as non-discrimination or robustness and safety to international discussion. Taken together with the fact that none of these principles are enforceable by law, it means that countries continue to have a lot of room for maneuver in their application of AI systems.

Second, the application possibilities for AI are too widespread for a one-fits-all approach. Different circumstances require different solutions. More specific application areas like manufacturing, surveillance, and the military need additional guidelines.

Third, ethics is always embedded in a cultural and social context that depends on a system of values shaped by a unique history. Since algorithms will impact many areas of our everyday lives, these cultural differences must be taken into account when drafting AI ethics. For instance, studies show that people in China and in the West have quite different responses to the famous “Trolley Dilemma,” a thought experiment in ethics that forces participants to make a difficult choice between a greater and a lesser evil.

Ultimately, such culture clashes will also be reflected in international politics. It will be a huge challenge to find common ground, especially if the international community seeks to develop more detailed principles and guidelines. Bringing in additional stakeholders and transferring what are ultimately ethical principles into hard law will be just as difficult.

Great Power Rivalry

Finally, and in addition to the challenges related to process, content, and implementation, there is a need to take the geopolitical context into account. This is true for the new technologies in general, but especially for general-purpose tools like AI. The great power rivalry between the US and China has only just begun, and emerging technologies with dual-use nature will be the main driver for economic profitability and military prowess. Hence, it is highly doubtful whether the so-called AI superpowers—first and foremost Beijing with its current demonstration of AI-based surveillance on minorities—will be willing to bind themselves in “ethical chains” through a self-imposed ethics regime. This is made evident by the reluctance of these countries to ban lethal autonomous weapons systems.

That is why it’s imperative that the EU continues to take the lead in the global debate on AI ethics in order to see the emergence of its “third way”—a digital sphere that is human-centered, regulated, and democratic. Yet setting high ethical standards is not enough. The EU and its member states also need to do more to establish a vibrant European AI ecosystem. This means not just encouraging additional investment, but also, among other measures, supporting European companies that develop AI systems. Otherwise, the EU will end up proclaiming and promoting detailed and sophisticated AI ethics guidelines without having any leverage to implement them internationally.

The post The Devilʼs in the Detail appeared first on Berlin Policy Journal - Blog.