89 Matching Annotations
  1. Jan 2021
  2. Dec 2020
    1. created with support from

      facial recognition art and awareness project

      ||MariliaM||

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    1. Among dozens of other “sensitive topics” listed were the oil industry, China, Iran, Israel, COVID-19, home security, insurance, location data, religion, self-driving vehicles, telecoms and systems that recommend or personalize web content.

      Here is the list of sensitive topics for Google PR. It will be interesting to analyse it further. Is there any document on this policy?

      ||Jovan||

    2. Google’s new review procedure asks that researchers consult with legal, policy and public relations teams before pursuing topics such as face and sentiment analysis and categorizations of race, gender or political affiliation, according to internal webpages explaining the policy.

      Google asked for positive 'spin' in the coverage of AI issues. It is intersting for a few reasons:

      • 'Ministry of truth' im making (Orwelian)
      • for our research on AI and media coverage as additional analysis of language/tone of articles
      • for language and diplomacy course

      ||Andrej|| ||kat_hone||||Katarina_An||||NatasaPerucica||||sorina||||djordjej||||JovanNj||

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    1. Unknown developers have made a program that emulates China’s Foreign Ministry spokeswoman Hua Chunying

      Mozda vam ovo bude interesantno u kontekstu naseg speech generatora. Nize u tekstu cete videti da je ovo bilo na GitHub-u, kao i simulaciju intervjua sa ministarkom Hua. ||Jovan||||JovanNj||||djordjej||||Katarina_An||

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    1. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big

      Paper that got Google AI ethics researcher fired outlines key risks associated with large language models - environmental and financial costs; massive data that oftentimes includes racist or abusive language and, because the datasets are so large, it is hard to audit them; large language models don't actually understand language, but excel at manipulating it, etc. ||Jovan||||djordjej||||NatasaPerucica||||JovanNj||

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    1. An interesting linkage between AI and nature. Potential use:

      • coverage on DW
      • research on digital and nature

      ||Jovan||||JovanNj||

    2. describing the algorithm that those networks extended to the way they learned from their mistakes, which is known as backpropagation.

      ||JovanNj|| An interesting concept of backpropagation.

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    1. To learn how modern voice assistants respond to direct queries about gender, we asked four of the most popular voice assistants on the market—Siri, Alexa, Cortana, and Google Assistant—about their gender identities.[3] We specifically chose to ask both open-ended and direct questions to understand the concepts programmed into the AI. We also asked if the voice assistants identified as non-binary to provide an option outside the traditional gender binary.

      testing gender identification in voice assistants

    2. In 2015, approximately 19.9% of students graduating with a U.S. bachelor’s degree in engineering identified as women, up from 19.3% in 2006.

      lack of women in stem vs bias

    3. oice assistants play a unique role in society; as both technology and social interactions evolve, recent research suggests that users view them as somewhere between human and object.

      views of ai assistants

    4. AI ethicist Josie Young recently said that “when we add a human name, face, or voice [to technology] … it reflects the biases in the viewpoints of the teams that built it,”

      useful quote

    5. he world may soon have more voice assistants than people—yet another indicator of the rapid, large-scale adoption of artificial intelligence (AI) across many fields.

      useful comparison

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    1. 3. Current Landscape for AI Standards

      A very good panorama of standardisation efforts on AI, updated until 2019. Of interest to the AI course. ||kat_hone||

    2. Standards will not achieve all AI policy goals, but they are a path towards effective global solutions wherenational rules may fall short. Standards can influence the development and deployment of particular AI systemsthrough product specifications for, i.a., explainability, robustness, and fail-safe design. They can also affect thelarger context in which AI is researched, developed, and deployed through process specifications. The creation,3dissemination, and enforcement of international standards can build trust among participating researchers, labs,and states.

      Interplay between the development of AI standards and achieving policy goals.

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  3. Nov 2020
    1. Humans have an inherent ability to learn novel concepts from only a few samples and generalize these concepts to different situations. Even though today’s machine learning models excel with an abundance of training data on standard recognition tasks, a considerable gap exists between machine-level pattern recognition and human-level concept learning

      machine learning pattern recognition vs human-level concept learning ||Jovan||||JovanNj|| ||NatasaPerucica||||djordjej||

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    1. human-level concept learning and reasoning. Humans beat #AI hands down!

      update AI coruse

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    1. Regulate AI only where required

      ||kat_hone|| cc ||Jovan||

      This article for your attention.

      Joshua is Chairperson of the Malta Digital Innovation Authority. Jovan has met with him in the past.

      I find he explains himself in a clear and informed way. He might be an asset in future events, also because in Malta (with its legislative agility) he gained some important experience.

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    1. fake people shared by ||Maja||

      ||JovanNj|| we may include it in the future AI presentations

      ||TerezaHorejsova||||Cecile||||MarcoLotti||

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    1. eventually boast an even deeper pool of data and experts to develop AI models.

      this presumption more data - more insights need to be revisited.

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    1. What about fake faces? How relevant it is for tomorrow's session?

      ||JovanNj||

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    1. US products are imported via third party traders or distributors, according to another investor in one of the AI unicorns

      import of US products

    2. Surveillance AI accounts for more than a half of all AI-powered applications

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    1. ‘Charter of Digital Rights’ as part of its leadership of the Council of the EU

      Discussion on EU member states' initatives on digital rights (Portugal to present a charter on digital rights, Germany's failed attempt to get member states to endorse AI and HR. ||Jovan|| ||StephanieBP||

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    1. Global Partnership on AI, a discussion forum at the OECD which seeks to define international principles for AI.

      another global partnership on defining rules on ai

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    1. Article explains why AI technology may not be as effective as it is proclaimed when it hits reality in medical field.

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    1. An excellent coverage in terms of communication and structure (good scientific journalism) with the following highlights:

      • focus on mapping neural neworks to brain around dealing with images, sound, and smell (three different types of challenges)
      • discusses limits in understanding functoinality of neural networks - it is the key aspect in our discussion on digital governance (to be used for our training on AI governance)

      ||JovanNj|| please add more comments on AI aspects ||VladaR||||kat_hone||||MariliaM||||Katarina_An||||NatasaPerucica||||markodj||||djordjej|| Let us use this for our training and research on AI governance and further developments of Diplo's AI systeem

    2. Artificial neural networks are built with interconnecting components called perceptrons, which are simplified digital models of biological neurons. The networks have at least two layers of perceptrons, one for the input layer and one for the output. Sandwich one or more “hidden” layers between the input and the output and you get a “deep” neural network; the greater the number of hidden layers, the deeper the network.

      A good explanation of neural networks.

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  4. Oct 2020
    1. A very interesting perspective that applies AI logic on social and political processes ||Jovan|| ||JovanNj|| ||NatasaPerucica|| ||djordjej|| ||kat_hone||

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    1. Facebook released a new open source translator which translates directly between language. It bypasses English as previously used 'bridge language' for translations from - for example - Chinese to French.

      ||JovanNj||||Cecile||||StephanieBP||||AndrijanaG||

    1. It is becoming clear that our Diplo5 focus is moving into right directions: a) focus on consolidating our data (Textus) b) integrating data value-add into our procedures (Textus) c) focusing on delivery of useful products (SpeechGen and Dta Sandbox).

      New possibilities will start opening with integration in this system of our LMS.

      ||Jovan||

    2. held back by Swiss data protection and cloud security laws

      why are people held back by Swiss data protection and cloud security laws?

      ||StephanieBP||||Pavlina||

    3. It is what Diplo has been doing with Textus and, soon, new storage system.

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    1. reflect on the huge attention generated by GPT-3 and what it heralds for the future research

      I haven't listened to this yet, but I'm curious how they reflect on GPT-3. Is the podcast just another way to feed the hype? ||MariliaM||||sorina.teleanu||||Jovan||||JovanNj||||djordjej||

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    1. Interesting text on the shift from a maturity-based to a risk-based cybersecurity. It discusses how this shift should translate into concrete measures within companies. Some elements could be interesting for course updates, including the security module on the AI course. Perhaps also interesting for cybersecurity ||VladaR||

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    1. This text is about the reasons why AI projects fail. Personally, I am not impressed by business/MBA lingo which is as cryptic as UN lingo.

      We developed Diplo 5.0 out of intuition, coincidence (pandemic crisis) and bit of good luck. But, according to this article, it seems that we got in optimal way by:

      • focusing on the purpose of AI
      • integration AI into regular work procedures of Diplo
      • use AI as part of transformation of Diplo
      • make smart mix of internal and external talents while integrating external talents into Diplo team.
      • having process managed by the director
      • have very low risks by using agile approach
      • have early deliverables (sometimes too early) is important for dynamics of the project.
      • make AI and data 'touchable' (non-AI people can realise what it is about; in this way we can addreess also fears and discuss AI in realistic context).
      • there is no off-the-shelf AI solution; one has to experiment a lot with testing, fast feedback, and constant adjustment.
      • focus on augmented intelligence via agile process interplaying machine and human intelligence (e.g. Speech Generator).
      • AI can help overcoming policy silos in a very effective ways.
      • we can learn a bit of 'AI lingo' for our communication with external organisatio (we should not internalise this language since it is often empty but we should be aware of itit.).

      All in all, our experience could be turned in this type of article in - I would say - even more effective way.

      ||Jovan||||JovanNj||

    2. AI-generated predictions, solutions, and perspectives enable theorganization to align around these new aordances. In short, while organizations often integratetheir data, processes, and behaviors to exploit AI opportunities more eectively, on the back ofthis work, successful AI applications have the potential to integrate the organization inunprecedented ways

      Interesting impact of AI on overcoming policy silos

    3. The underlying solution can get better because it learns from the human experts it augments."

      Diplo's approach

    4. they are people who are savvy enough about AI yet have acumen “in keybusiness areas, allowing our digital practice leaders to prioritize and deploy AI projects wherethey make the most sense.

      Key people for AI and digital transformation.

    5. Unify their AI initiatives with their larger business transformation eorts.• Invest in AI talent, data, and process change in addition to (and often more so than) AItechnology. They recognize AI is not all about technology.

      Two steps that were taken at Diplo.

    6. Integrate their AI strategies with their overall business strategy

      Diplo 5.0 approach of integrating AI in our activities.

    7. Signicant challenges remain, however. Many AI initiatives fail. Seven out of 10 companiessurveyed report minimal or no impact from AI so far. Among the 90% of companies that havemade some investment in AI, fewer than 2 out of 5 report business gains from AI in the pastthree years. This number improves to 3 out of 5 when we include companies that have madesignicant investments in AI. Even so, this means 40% of organizations making signicantinvestments in AI do not report business gains from AI

      Statistics about failure of AI projects.

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    1. Data Architects understand the organisation’s strategy and business problems to be solved, but have the technical insight to get their hands dirty in the data itself. They know what data is needed and how that data is to be integrated by various systems.

      Diplo 5.0 advanced a lot on data archtecture by combinaton of Textus - DigitalWatch - AI - LMS (to be added later on).

      ||Jovan||

    2. focus on cultural change and training within an organisation as it adapts to new working practices, but the most important factor is poor data.

      Integrating AI into working of organisation is the key challenge. If you have it, you have also good data (as result). Solving this cultural/organisational challenge is the main driver behind Diplo 5.0 evolutoin.

    3. Seventy percent of companies have reported minimal or no impact from Artificial Intelligence projects,

      Shocking statistics but realistic one.

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    1. Text provides useful mapping between philosophy and AI. It also applies some of dilemmas to real life situation (drug design and architecture). It tackles a bit 'my obsession' with choice and dilemma between efficiency and human autonomy.

      For Diplo We should broaden my writing/attempts to push forward philosophical aspects of AI. This is useful input. We should look for other philosphers/thinkers who provide contributions in this field. More specifical follow-up activities:

      ||kat_hone|| Put author at our speaker list for future events (could be simple GoogleDoc);

      ||Maja|| Follow-up with Aldo and Diplo Wisdom Circle (Jovan will write to Aldo.

      ||StephanieBP|| include in of the next issues of Weekly Digest

      ||sorina|| Add to AI page on DW; consider for next monthly briefing.

      ||Jovan|| Design 'philosophy' corner at DW which would reflect on these type of issues - will include interviews, coverage, etc.

      ||MariliaM||||kat_hone|| Consider input for AI course on philosophical reflections

      ||JovanNj|| Input for Belgrade's AI discussions on bridges between AI - philosophy religion (||NatasaPerucica|| to follow-up with Father Romilo

    2. Norman Sieroka (University of Bremen // ETH D-CHAB)

      ||kat_hone|| We may invite him as a speker for our future events on AI and philosphy.

    3. “to coordinate the current expressions of human experience

      What is philosophy?

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  5. Sep 2020
    1. Here is a summary of the article on GPT-3 published in Guardian:

      • GPT-3 identifies patterns and generate sentences.
      • humans are in control
      • discarded 90% of text generated by GPT-3
      • humans had to write prompt and edit generated text.

      ||Jovan||

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    1. Countries with limited capacity to transform digital data into digital intelligence are constrained in their potential to capture economic value from data. To prevent dependence on a small group of advanced countries in the increasingly data-driven economy, national development strategies need to include digital upgrading (value addition) in data value chains. This would enhance domestic capacities to move from treating data as raw material to processing digital data and using artificial intelligence. It may involve designing national data policies and strategies to seize opportunities that the expansion of data can create, and manage associated risks and challenges

      Transforming data into intelligence

    2. POLICIES AND STRATEGIES TO CLOSE THE DIGITAL DIVIDE AMONG AND WITHIN COUNTRIESInnovation policy

      Take into account when updating the e-commerce and AI course

    3. FIGURE 5.2 LARGE PARTS OF THE WORLD ARE MISSING OUT ON TECHNOLOGY CREATION AND USE

      For the AI and e-commerce course. ||kat_hone|| it could be useful to you as well.

    4. illustrates two salient features in the creation and use of frontier digital technologies for production. First, large parts of the world, especially on the African continent, remain completely excluded.3 These countries are not even importing any significant volumes of the most representative goods. Second, even among countries with some activity in frontier digital production technologies, the roles are quite diverse. Latecomers, for instance, are entering the race, but it is not yet clear if they will become followers. Among the followers, a large number are mainly importing capital goods produced aboard, with very little or no domestic innovation and few exports. Their prospects to advance are limited, as this will require large investment

      Figures on the creation and use of frontier digital technologies: advanced robotics, computer-aided manufacturing, additive manufacturing and machine learning. ||Jovan||

    5. These top economies account for almost all global activity in each area – above 90 per cent.

      Patents, imports and exports of advanced technologies. Interesting amount and the chart that follows is also very interesting.

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    1. AI value pyramid

      a new term? ||kat_hone||

    2. ‘data’ to ‘knowledge.’

      The paradigm shift - this is the first time in mainstream media that I've came across this focus on knowledge instead of data. We are visionaries as always :)

      ||Jovan|| ||JovanNj|| ||Katarina_An|| ||kat_hone|| ||NatasaPerucica||

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    1. We want a set of rules that puts people at the centre.  Algorithms must not be a black box and there must be clear rules if something goes wrong. The Commission will propose a law to this effect next year.

      Rules on AI.

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  6. Aug 2020
    1. But unless we’re very careful, AI systems won’t see that - they’ll just learn about the world as it is, with all its unfairness and inequality, not the world as we want it to be. And they’ll dedicate their intelligence to reproducing the past, not to creating a brighter future

      Principle of garbage in, garbage out. Inequalities and all.

    2. For instance, the BigMedilytics project – which is funded by the EU – has used AI to improve the treatment of some of the 15 million Europeans who live with heart failure

      AI for health

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    1. Fake audio or video content

      Deepfakes ranked as the most serious AI crime threat, followed by driverless vehicles, AI-powered spear phishing, fake news, etc. ||djordjej|| ||NatasaPerucica|| ||Jovan|| ||VladaR||

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    1. a study by Roland Berger f

      useful data resource on investment in AI

      ||Jovan|| ||djordjej|| ||Katarina_An||

    2. ‘cybercolonies’

      Interesting terminology for the EU as a 'third world entity' in the digital world. This also links to the MIT article on AI colonialism.

      ||Jovan||

    3. In the German case, the focus on European – specifically, Franco-German – cooperation, appears to be a goal in itself, or the default idea. The French strategy, in contrast, adopts a more pragmatic approach – supporting European cooperation only in areas in which the strategy’s authors consider it to be useful.

      On German and French national AI strategies (different perceptions of the EU approach)

      ||sorina|| ||sorina.teleanu||

    4. There are several reasons one cannot just ‘take the EU’s word for it’

      On EU's approach to AI and why there can never really be a 'single EU' position on AI (EU institutional structure, use of AI in the military sector...) ||Jovan|| ||sorina||

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    1. Features

      New application. Let us experiment with this app for summarising information.

      ||Jovan||

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    1. How to build decolonial AI

      potential principles for AI but could extend to data

      ||Jovan|| ||Katarina_An|| ||MarcoLotti||

    2. This has played out in the recent rush to form global AI ethics guidelines: developing countries in Africa, Latin America, and Central Asia have been largely left out of the discussions, which has led some to refuse to participate in international data flow agreements.

      interesting point for Road to Bern initiative and work on data principles/values

      Why developing countries are refusing to participate in international data flow (India refused to sign the G20 Osaka Declaration on data flow).

      ||Jovan|| ||Katarina_An|| ||MarcoLotti||

    3. “decolonise artificial intelligence”—to reorient the field’s work away from Western hubs like Silicon Valley and engage new voices, cultures, and ideas for guiding the technology’s development.

      Drawing parallels between biased AI/discriminating algorithms with concentration of AI knowledge and expertise. ||Jovan|| ||djordjej|| ||Katarina_An|| ||sorina|| ||JovanNj||

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  7. Jul 2020
    1. everyone could use themas part of our Open Compute Project.

      Can we use this type of computers for our AI processing? ||JovanNj||

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    1. The panel will then make a decision by the end of the year on whether a legally binding treaty should go ahead

      On regulation of AI and possible a legally binding treaty prepared by the CoE

      ||sorina|| ||sorina.teleanu|| ||Jovan||

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    1. GPT-2 was described as a “chameleon-like” synthetic text generator, but it wasn’t state-of-the-art in downstream tasks like question answering, summarization, or translation.

      It is an interesting point of difference between text generation, question answering, summarization or translation? Here, we can discuss a potential usability of GPT-2 ||JovanNj||||djordjej||||NatasaPerucica||||Katarina_An||

    2. GPT achieved state-of-the-art in language tasks by pairing supervised learning with unsupervised pre-training (or using the parameters from an unsupervised step as a starting point for the supervised step).

      How can GPT perform supervised and unsupervised pre-training? How it can work practiclally? ||JovanNj||||Jovan||

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    1. AI is far more dangerous than nukes."

      And what about drawing parallels with nuclear deterrence. The logic of Paul Ramsey (babies tied to front bumpers) may be interesting to consider here too. ||Jovan|| ||djordjej||

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    1. Microsoft last week announced features that will help users enable team mode, where they can sit together in a different environmen

      Microsoft to develop team mode (a virtual background feature that shows everyone together (impression that they're sitting in the same room)) in video conference. Can draw parallels between small vs large diplomatic delegations

      ||Jovan|| ||djordjej|| ||VladaR||

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    1. It is our responsibility to recognize our skewed perspective and listen to those impacted by AI.

      valid point, AI researchers being biased towards their own profession

      ||sorina|| ||Jovan|| ||djordjej||

    2. Don’t ask if artificial intelligence is good or fair, ask how it shifts power

      She argues that those usually excluded should be included by the AI community thus contributing to the shift in power

      Does AI serve only the powerful? What about the data subject, what is their say in AI?

      ||Jovan|| ||djordjej|| ||sorina||

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    1. Open UN GGE and UN OEWG issues

      ||JovanNj|| Here is another example of an interplay questions/answers.

      ||AndrijanaG|| ||VladaR|| ||StephanieBP||

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    1. The first is distrust of the state by many young Oromos, who argue it has long been dominated by smaller groups such as Tigrayans and Amharas.

      ?Q Why are young Oromos distrustful of the Ethiopian state?

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    1. 1

      ?Q: What about using interviews as an input into DiploAi system like this interview. In a way we have ready made Q&A. Shall we identify somehow this type of resoruces for further by our system (could you suggest some coding procedure in order to identify and extract this type of resources).

      ||JovanNj|| ||NatasaPerucica|| ||djordjej|| ||VladaR|| ||Jovan||

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  8. Jun 2020
    1. Today, during Road to Bern meeting they mentioned Kaggle platform as solution for a problem I outlined (how to bring togehter various datasets and discover correlations).

      ||djordjej|| developed this functionality - as prove of concept - in GoogleSheets. Djordje, please send us description and links.

      ||Jovan||

    <