Wong’s Solutions
16. Micronsoft
Executive Summary
The low barriers to entry of e-platforms have engendered the modern democratisation of media. Swathes of
information inevitably come with large volumes of falsehoods (including “deepfakes” and synthetic online media) andusers tend to be insufficiently aware of their accuracy. This leads to propagation of fake news which may stymie social
cohesion and incite political polarisation. Wong’s Solutions strives to enable individuals, enterprises and governments
to verify the veracity of stories through the AI-empowered and community-oriented application, Jairus. We capitaliseon AI-based algorithms while attracting users by rewarding them for actively contributing to our product’s accuracy,addressing the prohibitive costs, low scalability and insufficient confidence in manual fact-checking initiatives.
Product Summary
Jairus is a unified interface synthesising modern technologies and community-based
truth-verification methods to combat misinformation on various mediums. For
textual/audio inputs, our AI model extracts keywords, comparing it against credible
sources updated via government information. Our Multiple Natural Language
Processing Embedding models then calculate similarities between inputs and sourcesof credible information. Technical measures like randomising IP addresses and UID
tokens will also be used to reduce the possibility of obtaining biased results due totrackers and cookies. For images/videos, specialised AI models can be employed todetect possibly altered images and videos using technologies like DeepFake. Using
the DeepFake algorithm and similar image altering techniques, our models will be trained as adversarial learningalgorithms which reverse engineer the distortion process and identify its weaknesses. Finally, we combine outputs fromthe 4 domains into a multi-modality AI model, generating a holistic “trustworthiness” rating.1 This comprehensive
coverage of data is applicable to all mediums, even offline outlets like radio and television. Content above the 70th
percentile for “falseness” will be flagged as fake news.
This interface will be available as a website/extension at the following prices,with large-scale institutions like firms and governments charged less.
Moreover, an iterative, community-based system can enhance the long-term
reliability of these algorithms while boosting consumer trust. Users disagreeing
with “trustworthiness” ratings of various content can flag them - when more than
20% of viewers flag a post, our central staff will rigorously review its validity. Users who accurately identify content
with inaccurate ratings are rewarded with digital tokens; each can be exchanged for $0.01 or accumulated for discounts
on our products. This increases user participation and trust while providing greater sample data for our model’s
Recurrent Neural Networks and Long Short-Term Memory Deep Learning methods, boosting its accuracy.2
Market Research
The trustworthiness of current social media fact-checking services is largely dependent on their origin.3 Consumers
harbour doubts over the impartiality of fact-checked information owing to the profit-maximising aims of social media
companies such as Meta and Twitter and the lack of transparency over algorithms used.4 Another shortcoming is thelargely unidirectional process of user interaction that does not involve the direct beneficiaries of such services,
accentuating the need for a more credible and community-oriented service.

1

https://arxiv.org/abs/2205.09817
https://www.scirp.org/journal/paperinformation.aspx?paperid=109149
3
https://www.researchgate.net/publication/319254280_Trust_and_Distrust_in_Online_Fact-Checking_Services
4
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2301235
2

Existing competitors such as Fact Checker by the Washington Post and UK-based Full Fact are inherently inefficient asthey do not share repositories. The lack of a universal fact-checking database5 leads to inefficiency considering theoverwhelming volume of disinformation. This leads to less scalable and more labour-intensive business models,rendering such operations unsustainable.6 However, the fact-checking market is now dominated by established news
outlets such as Agence France-Presse and Reuters who have access to their own information databases.7 This is apotential limitation because the streamlined process of obtaining information is a feature that our solution does not
enjoy in the initial stages of development. Nevertheless, this entails that our product will be comparatively impartial
since our data stem from a broad range of sources, gleaned from by our AI-powered algorithm.
Marketing Strategy
Our progressive marketing strategy promotes Jairus to 2 target audiences: (1) the general public and (2) social media
companies. Step 1 is to increase visibility of our product to the general public through targeted advertising on social
media and the Internet. The focus of our advertisements is to explicitly highlight our primary product advantage --- theseamless integration of cutting-edge technology and community participation. We will place emphasis on our uniquetoken reward scheme, enabling users to play a part in the algorithmic process of our fact-checking service throughflagging posts they disagree with online. This sense of ownership and involvement makes users feel valued, building
public confidence and enhancing our service’s credibility.8
Step 2 specifically targets media enterprises. We will pitch our solution as an industry-leading tool crucial in allowing
them to verify primary sources upon which their reporting will be based. Furthermore, we can leverage on a solid userbase and fact-checking community built from Step 1. By raising awareness and underlining the importance of objective
fact-checking, there is likely to be an increase in demand by users for social media firms to ensure that publishedcontent is accurate. This exerts pressure on firms to purchase our AI fact-checking service to present a sociallyresponsible public image of themselves, catering to consumer preferences to grow their user base.9
Another key competitive advantage of having a sizable user base is the reaping of internal economies of scale as themarginal cost of hosting new users (in terms of server infrastructure upkeep) falls when total volumes increase, thereby
addressing current market inefficiency due to the disjointedness of individual fact-checking organisations.
Financial Plan
To finance our business’ initial start-up costs, a mix of coupon bonds(39.1%), convertibles (26.1%) and equity (34.8%) will be used. As
approximated by our Discounted Cash Flow (DCF) model, coupon
bonds ($13500) will primarily be bought by governments given thepositive externalities of combating misinformation;10 equity ($12000)
will be offered to private investors seeking high returns for a low-cost
investment; convertibles ($9000) providing a balance between
security (fixed coupons) and potential upside (convertible element)
will be offered to both.
While our product is unlikely to turn a profit during initial years due
to high start-up costs, we project that the company will turn over a profit by its 4th financial year as revenues steadily
increase. Meanwhile, our flexible financing plan also ensures the maintenance of a positive cash flow throughout theproduct’s development to sustain necessary operations.
5

https://www.cits.ucsb.edu/fake-news/protecting-ourselves-fact
https://www.poynter.org/fact-checking/2016/why-do-fact-checking-sites-close-and-how-can-new-ones-avoid-that-fate/.
7
https://factcheck.afp.com/fact-checking-afp
8
https://www.health.state.mn.us/communities/practice/resources/chsadmin/community-relationships.html
9https://www2.deloitte.com/us/en/insights/industry/technology/study-shows-news-consumers-consider-fake-news-a-big-problem.html
10https://cordis.europa.eu/project/id/780355
6