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Startups Creating Tools To Monitor AI and Promote Ethical AI Usage

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Startups Creating Tools To Monitor AI and Promote Ethical AI Usage

Over the course of the past year, it seems that more and more attention is being paid to ensuring that AI is used in ethical ways. Google and Microsoft have both recently warned investors that misuse of AI algorithms or poorly designed AI algorithms presents ethical and legal risks. Meanwhile, the state of California has just decided to pass a bill that bans the use of face recognition technology by California’s law enforcement agencies.

Recently, startups such as Arthur have been attempting to design tools that will help AI engineers quantify and qualify how their machine learning models perform. As reported by Wired, Arthur is trying to give AI developers a toolkit that will make it easier for them to discover problems when designing financial applications, like unveiling bias in investment or lending decisions.

Arthur’s efforts are aimed at addressing the “black box” problem of AI. The black box problem in AI describes how unlike traditional code, which can be easily interpreted by those who know how to read it, machine learning systems map features to behavior without unveiling the reasons that these behaviors are selected/how the features have been interpreted. In other words, in a black box system the exact implementation of the algorithm is opaque.

Machine learning systems operate by extracting patterns from input data and reasoning about these patterns. This is accomplished by essentially having a computer write its own code by manipulating certain mathematical functions. In order to address this problem, researchers and engineers need tools that make the observation and analysis of machine learning software behavior easier. Startups like Arthur acknowledge the difficulty of solving this problem and don’t claim to have the optimal solutions, but they are hoping to make progress in this area and make cracking open the black box a little easier. Its hoped that if AI systems can be analyzed easier, it will become easier to correct problems like bias as well.

Large companies like Facebook already have some tools to analyze the inner workings of machine learning systems. For example, Facebook has a tool dubbed Fairness Flow which is intended to make sure the ads that recommend jobs to people target people from all different backgrounds. However, it is likely that large AI teams won’t want to invest time in creating such tools, and therefore a business opportunity exists for companies that want to create monitoring tools for use by AI companies.

Arthur is focused on creating tools that enable companies to better maintain and monitor AI systems after the system has already been deployed. Arthur’s tools are intended to let companies see how their system’s performance shifts over time, which would theoretically let companies pick up on potential manifestations of bias. If a company’s loan recommendation software starts excluding certain groups of customers, a flag could be set that indicates the system needs review in order to ensure it isn’t discriminating against customers based on sensitive attributes like race or gender.

However, Arthur isn’t the only company creating tools that let AI companies review the performance of their algorithms. Many startups are investing in the creation of tools to fight bias and ensure that AI algorithms are being used ethically. Weights & Biases is another startup creating tools to help machine learning engineers analyze potential problems with their network. Toyota has used the tools created by Weights & Biases to monitor their machine learning devices as they train. Meanwhile, the startup Fiddler is working to create a different set of AI monitoring tools. IBM has even created its own monitoring service called OpenScale.

Liz O’Sullivan, one of the co-creators of Arthur, explained that the interest in creating tools to help solve the Black Box problem is driven by a growing awareness of the power of AI.

“People are starting to realize how powerful these systems can be, and that they need to take advantage of the benefits in a way that is responsible,” O’Sullivan said.

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Regulation

Google’s CEO Calls For Increased Regulation To Avoid “Negative Consequences of AI”

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Google's CEO Calls For Increased Regulation To Avoid "Negative Consequences of AI"

Last year saw an increasing amount of attention drawn to the regulation of the AI industry, and this year seems to be continuing the trend. Just recently, Sundar Pichai, the CEO of Google and Alphabet Inc., supported the regulation of AI at an economic think tank taking place in Brugel.

Pichai’s comments were likely made in anticipation of new EU plans to regulate AI, which will be revealed in a few weeks. It’s possible that the EU regulations could contain policies legally enforcing certain standards for AI used in transportation, healthcare, and other high-risk sectors. The new EU regulations may also require increased transparency regarding AI systems and platforms.

According to Bloomberg, Google has previously tried to challenge antitrust fines and copyright enforcement in the EU. Despite previous attempts to push back against certain regulatory frameworks in Europe, Pichai stated that regulation is welcome as long as it takes “a proportionate approach, balancing potential harms with social opportunities.”

Pichai recently wrote an opinion piece in Financial Times, where he acknowledged that along with many opportunities to improve society, AI also has the potential to be misused. Pichai stated that regulations should help avoid the “negative consequences of AI”, citing abusive use of facial recognition and deepfakes as negative applications of AI. Pichai stated that international alignment is necessary for regulatory principles to work, and as such, there needs to be agreement on core values. Beyond that, Pichai said that it is the responsibility of AI companies like Google to give consideration to how AI can be used in an ethical manner and that this is why Google adopted its own standards for ethical AI use in 2018.

Pichai stated that government regulatory bodies and policies will play an important role in ensuring AI is used ethically, but that these bodies need not start from scratch. Pichai suggests that regulatory entities can look to previously established regulations for inspiration, such as Europe’s General Data Protection Regulation. Pichai also wrote that ethical AI regulation can potentially be both broad and flexible, with regulation providing general guidance that can be tailored for specific implementations in specific AI sectors. Newer technologies like self-driving vehicles will require new rules and policies that weigh benefits and costs against one another, while for more well-tread ground like medical devices, existing frameworks can be a good starting point.

Finally, Pichai stated that Google wants to partner with regulators to develop policies and find solutions that will balance trade-offs, Pichai wrote in Financial Times:

“We want to be a helpful and engaged partner to regulators as they grapple with the inevitable tensions and trade-offs. We offer our expertise, experience and tools as we navigate these issues together.”

While some have applauded Google for taking a stance on the need for regulation to ensure ethical AI usage, the debate continues over the extent to which it’s appropriate that AI companies should be involved with the creation of regulatory frameworks.

As for the upcoming EU regulations themselves, it’s possible that the EU is pursuing a risk-based rules system, which would put tighter restrictions on high-risk applications of AI. This includes restrictions that could be much tighter than Google hopes for, including a potential multi-year ban on facial recognition technology (with exceptions for research and security). In contrast to the EU’s more restrictive approaches, the US has pushed for relatively light regulations. It remains to be seen how the different regulation strategies will impact AI development, and society at large, in the two different regions of the globe.

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U.S. Government Will Limit Exports of Artificial Intelligence

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U.S. Government Will Limit Exports of Artificial Intelligence

The U.S. government will take steps next week to limit the export of artificial intelligence (AI) software. The decision by the Trump administration comes at a time when powerful rival nations, such as China, are becoming increasingly dominant in the field. The move is meant to keep certain sensitive technologies from falling into the hands of those nations. 

The new rule goes into effect on January 6, 2020,  and it will be aimed at certain companies that export geospatial imagery software from the United States. Those companies will be required to apply for a license to export it. The only exception is that a license will not be required to export to Canada. 

The new measure was the first of its kind to be finalized by the Commerce Department under a mandate from a 2018 law passed by Congress. That law updated arms controls to include emerging technology. 

The new rules will likely have an effect on a growing part of the tech industry. These algorithms are currently being used in order to analyze satellite images of crops, trade patterns and other changes within the economy and environment. 

Chinese companies are responsible for having exported artificial intelligence surveillance technology to over 60 countries. Some of those countries have dismal human rights records and include Iran, Myanmar, Venezuela, and Zimbabwe. 

Within the nation of China itself, the Communist Party is using facial recognition technology systems to target Uighurs and other Muslim minorities located in China’s far western Xinjang region. According to a report released by a U.S. think tank, Beijing has been involved in “authoritarian tech.”

The think tank that released the report was the Carnegie Endowment for International Peace, and they did so after rising concerns of authoritarian regimes using the technology as a way to gain power. 

“Technology linked to Chinese companies — particularly Huawei, Hikvision, Dahua and ZTE — supply AI surveillance technology in 63 countries, 36 of which have signed onto China’s Belt and Road Initiative,” the report said.

One of China’s leading technology companies, Huawei Technologies Co., alone provides AI surveillance technology to at least 50 countries. 

“Chinese product pitches are often accompanied by soft loans to encourage governments to purchase their equipment,” according to the report. “This raises troubling questions about the extent to which the Chinese government is subsidizing the purchase of advanced repressive technology.”

China has faced increased scrutiny after an investigative report by the International Consortium of Investigative Journalists was released detailing the nation’s surveillance and policing systems, which are being used to oppress Uighurs and send them to internment camps. 

The new rules implemented by the U.S. government will at first only go into effect within the country. However, U.S. authorities have said that they could be submitted to international bodies at a later time. 

There has been recent bi-partisan frustration over the long amount of time it is taking to roll-out new export controls for the technology. 

“While the government believes that it is in the national security interests of the United States to immediately implement these controls, it also wants to provide the interested public with an opportunity to comment on the control of new items,” according to Senate Minority Leader Chuck Schumer.

 

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Ethics

AI Now Institute Warns About Misuse Of Emotion Detection Software And Other Ethical Issues

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AI Now Institute Warns About Misuse Of Emotion Detection Software And Other Ethical Issues

The AI Now Institute has released a report that urges lawmakers and other regulatory bodies to set hard limits on the use of emotion-detecting technology, banning it in cases where it may be used to make important decisions like employee hiring or student acceptance. In addition, the report contained a number of other suggestions regarding a range of topics in the AI field.

The AI Now Institute is a research institute based at NYU, possessing the mission of studying AI’s impact on society. AI Now releases a yearly report demonstrating their findings regarding the state of AI research and the ethical implications of how AI is currently being used. As the BBC reported, this year’s report addressed topics like algorithmic discrimination, lack of diversity in AI research, and labor issues.

Affect recognition, the technical term for emotion-detection algorithms, is a rapidly growing area of AI research. Those who employ the technology to make decisions often claim that the systems can draw reliable information about people’s emotional states by analyzing microexpressions, along with other cues like tone of voice and body language. The AI Now institute notes that the technology is being employed across a wide range of applications, like determining who to hire, setting insurance prices, and monitoring if students are paying attention in class.

Prof. Kate Crawford, co-founder of AI Now explained that its often believed that human emotions can accurately be predicted with relatively simple models. Crawford said that some firms are basing the development of their software on Paul Ekman’s work, a psychologist who hypothesized there are only six basic types of emotions that register on the face. However, Crawford notes that since Ekman’s theory was introduced studies have found that is far greater variability in facial expressions and that expressions can change across situations and cultures very easily.

“At the same time as these technologies are being rolled out, large numbers of studies are showing that there is… no substantial evidence that people have this consistent relationship between the emotion that you are feeling and the way that your face looks,” said Crawford to the BBC.

For this reason, the AI Now institute argues that much of affect recognition is based on unreliable theories and questionable science. Hence, emotion detection systems shouldn’t be deployed until more research has been done and that “governments should specifically prohibit the use of affect recognition in high-stakes decision-making processes”. AI Now argued that we should especially stop using the technology in “sensitive social and political contexts”, contexts that include employment, education, and policing.

At least one AI-development firm specializing in affect recognition, Emteq, agreed that there should be regulation that prevents misuse of the tech. The founder of Emteq, Charles Nduka, explained to the BBC that while AI systems can accurately recognize different facial expressions, there is not a simple map from expression to emotion. Nduka did express worry about regulation being taken too far and stifling research, noting that if “things are going to be banned, it’s very important that people don’t throw out the baby with the bathwater”.

As NextWeb reports, AI Now also recommended a number of other policies and norms that should guide the AI industry moving forward.

AI Now highlighted the need for the AI industry to make workplaces more diverse and stated that workers should be guaranteed a right to voice their concerns about invasive and exploitative AI. Tech workers should also have the right to know if their efforts are being used to construct harmful or unethical work.

AI Now also suggested that lawmakers take steps to require informed consent for the use of any data derived from health-related AI. Beyond this, it was advised that data privacy be taken more seriously and that the states should work to design privacy laws for biometric data covering both private and public entities.

Finally, the institute advised that the AI industry begin thinking and acting more globally, trying to address the larger political, societal, and ecological consequences of AI. It was recommended that there be a substantial effort to account for AI’s impact regarding geographical displacement and climate and that governments should make the climate impact of the AI industry publically available.

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