Master Thesis: Building an explainable AI algorithm to detect Fake News & MisInformation Propagandas

Unbiased Gothenburg StudentPart-time
Salary Competitive

Unbiased is a deep tech startup determined to challenge the complex societal issues and to build next-generation business models with next-generation technology. Some of the problems we are addressing include Fighting Bias in AI, Fighting Fake News & Misinformation on the Internet. We love to encourage and work with passionate individuals who are crazy about innovation, technology and driven to do something good for the benefit of others.


Master Thesis - Building an explainable AI algorithm to detect Fake News & Mis-Information Propagandas [Including AI-generated content a.k.a deep fakes]


The goal of this master thesis work is mainly focused on evaluating the existing research in the field of AI algorithms to Fight Fake News & Misinformation and to develop new AI algorithms that address the problem & supports explainability. This Master Thesis Project is performed in collaboration between Alten IT & Unbiased.


Fake News and Misinformation is a big problem in our society today, it's not only affecting our decision-making process but also killing people in some scenarios. We believe that the contribution of technology advancements in AI and the current social platforms are part of the problem. We also believe that one single solution cannot address the problem but it will limit the impact and educate users. In the last year or two, there have been many advancements in this domain and as part of our mission at Unbiased, we would like to contribute in the fight by innovating and developing new solutions.


Key Requirements:

  • Masters Student with Computer Science background based in Göteborg.

  • Driven to innovate.

  • Good hands-on experience with programming & web technologies.

  • Experience in Python

  • Experience working with TensorFlow or similar frameworks

  • Comfortable in finding the datasets, asking questions and taking initiatives


Expected Outcomes:

  • 4-5 articles addressing the problems, challenges and existing solutions.

  • Detailed theoretical analysis report presenting the research landscape in this domain.

  • An algorithm built based on the identified research gap.

  • Master Thesis report

  • An end-to-end ready to use tool with built-in API endpoints presents the research work.

For more information or questions please contact us at contact@unbiased.cc

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Unbiased

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Our Motto: Fighting fake news and misinformation on the Internet using technology. At Unbiased, everything we do, we believe in challenging the status quo of how we use the technology. We believe in thinking differently. We envision the true essence of a transparent and democratic world where every individuals’ opinion matters. The way we challenge the status quo is by making the applications we build transparent, simple to use and innovative. By doing so, we believe that we will move forward altogether towards a healthy society where transparency, trust, and quality are valued. ------------------------------------------------------------------------------------- Unbiased AB is a tech company based in Sweden, Fighting Fake News and Misinformation with a focus on futuristic innovation and next-generation technology. The areas we are focused on currently include Blockchain technology, Machine Learning, Artificial Intelligence, and Natural Language Processing. It's no secret that the current social media and Internet platforms have many flaws when it comes to transparency, privacy, and false information. With increasingly biased news in traditional media combined with false information on the Internet, people across the globe are not able to make decisions based on reliable data and insights. Fake News is not only affecting us as individuals but also our communities at large. We are addressing the problem of Bias in technology, Fake news and the fact that it is difficult to follow up on the origin of news, data, and information. We are approaching this complex problem in a staged manner whereby we start at the core algorithm level of applications and we scale to the end-user interaction level. We believe that one single solution cannot address this issue, the only way to address this problem is by educating people, enterprises, communities and empowering them with necessary tools & solutions.

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