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Privacy & Security
- Personal data is collected unconsciously or without user consent
- Users have no idea about who can access to the data and what they will do with it
- Data is the most precious asset in the digital society and its value continues growing
- Users who generate data get no reward from the value their data creates
- Forthcoming privacy regulations e.g. GDPR could be a huge challenge for companies
- There is no standard solution yet to deal with the challenge
- Integrate human intelligence with machine intelligence to make AI smarter
- Give users full access to and control of personal data
- Users can set trade-offs between data privacy and service personalization
- We collaborate with MIT Open Algorithms (OPAL) and extend it towards mobile devices
- Raw data stays on users’ devices with publicly verifiable code running on top
- Only aggregated knowledge or algorithm outputs will be shared with data consumers
- Control access to personal data and user account in the ecosystem
- Guarantee data integrity as well as data availability
- Ensure secure token storage and automated payments
The ecosystem is separated into a user space and a service space by blockchain. The user space controls all interactions with end users and deals with data collection, aggregation, and encryption. Blockchain and insight storage take care of data transfer and token transaction. The service space, on the other hand, conveys aggregated knowledge and/or user feedbacks to data consumers and business applications.
Prof. Alex Sandy Pentland, MIT
The Human Strategy. A Conversation with Alex "Sandy" Pentland on Edge.org [10.30.17].
Personal Data and Use Cases
An AR game publisher wants to do mobile marketing among users who have already played AR games. We can help it identify these users directly through checking app logs or indirectly through predicting personal interests based on other mobile data. Furthermore, how a user spends his/her time on various apps can be derived, which leads to knowledge about the user’s attention on smartphones and how it evolves over time.
The cryptocurrency market is growing rapidly and many investors use mobile apps like Coin Market Cap to track performance of investment. In-app personal data, such as each user’s portfolio, can be shared on social media but not yet monetized. With our SDK, anyone can publish his/her portfolio and users who want to follow top-performing investors will have access to the data after paying a fee to the data publisher.
A healthcare company hypothesizes that a user’s activity on smartphone well reflects the user’s stress. Human-AI framework can be utilized to gather data on how people use smartphones, but scientific rigor requires ground-truth to assess their stress levels. Our SDK facilitates this by sending users questionnaires to sample real-time stress levels. The company can develop models to predict stress and apply treatments to improve users’ mental health.
1. Unlocking Mobile Personal Data
Our first product aims at unlocking and monetizing mobile personal data on mobile devices. Each user’s mobile attention, which means how s/he spends time on different mobile apps, will be our focus in the beginning of development. Other types of mobile personal data such as location and movement, as well as user feedback data will also be unlocked in the product.
2. Mobile SDK to Scale up
The second product is a mobile SDK, with which businesses can integrate existing apps into the Human-AI ecosystem. It also helps them stay in compliance with new data regulations such as GDPR. The SDK provides the same features as the first product, but with extended data type, i.e., in-app data. Consequently, users will be able to share and monetize personal data in any mobile app.
3. Moving towards AR / MR
We believe that AR/MR will become the next generation consumer electronics. In addition to smartphone data, AR provides opportunities for better user interaction and personalization. For example, it empowers eye tracking on the one hand and real-time image recognition on the other hand. This helps to understand more precisely about each user’s actual attention and interest.
The HAI Token
- Token Symbol: HAI (ERC20 Token)
- Hard Cap: $20 Million
- Total HAI Created: 1,000,000,000
- Max. Units of HAI Sold: 400,000,000
- Pre-Sale Launch Time: 2018 Q2
- Public-Sale Launch Time: 2018 Q3
40% Sold during TGE
25% User Adoption & Incentives
20% HumanAI (vesting over 2 years)
10% Partnerships & Community
5% TGE Costs & Bounty Program
Milestones & Roadmap
1. CTI Grant Fund for Research in Mobile Personal Data
Started research activities in mobile personal data and relevant business cases at ETH Zurich and University of St. Gallen. Grant fund from the National Commission for Technology and Innovation in Switzerland (CTI).
First Prototypes for Collecting Mobile Personal Data
Started to build first prototypes for collecting mobile personal data and released mobile apps in Google Play Store.
2. CTI Grant Fund for Research in Mobile Personal Data
Second grant fund from the National Commission of Technology and Innovation in Switzerland (CTI).
Conception and Development of the OPAL system (paradigm of open algorithms) by the Human Dynamics group of Professor Alex “Sandy” Pentland at MIT Media Lab.
Cooperation Center for Digital Health Interventions
Start of cooperation with the Center for Digital Health Interventions at ETH Zurich and University of St. Gallen.