building an engine for tokenized ranking algorithms
TRANSCRIPT
NOTIO
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Building an Engine for Tokenized Ranking Algorithms
Enabling New Business Models for the Online Media Industry
Maciej Olpinski | userfeeds.io co-founder
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Bitcoin has proven it’s possible to:
👉 influence human behaviours 💰 using economic incentives
💻 embedded in open source software 🕸 …and achieve sustained economic
coordination Large numbers of people will do the same things because they
own or want to own valuable tokens.Global coordination through incentive alignment.
Human attention is allocated by middlemen & opaque algorithms.Proprietary, for-profit algorithms determine what’s happening inside our minds.
closed data
data reputation algorithm
Problem:
fake news, hate, clickbait, spam, online governance, ad targeting
are information ranking problems
diverse problems such as
⬆⬇
in the XXI century ‘attention economy’ - the control of popular rankings (GOOG/FB) translates to economic and political power
what is an advertising platform?an alternative definition
a platform for content ranking algorithms which use USD/EUR paid to the platform owner as a signal
for ranking of information selected by the advertiser
💰 💰 💰 💰
⭐⭐⭐ Could ranking algorithms allocate your attention using signals that
you can ‘own’?
Can we do for ranking algorithms what Bitcoin did for money?
💡 tokens prove that it’s possible to have economic moats
around network effectswith open codeand open data
withusers-as-stakeholders
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Token
How much would you pay for ‘Token’ in 1998
if Google used it as a ranking factor in Adwords?
The amount of token you hold
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💰 There are two revenue streams for media companies today:
- sell advertising - user is a product, advertiser is a customer- sell subscriptions - content is a product, reader is a customer
- sell token - access to the network’s attention is the product, user is a stakeholder
we want to enable a 3rd revenue stream:
⭐⭐⭐ We’re building an engine for ranking algorithms
that use tokens as ranking signals
⬆⬇ Our goal is to enable new business models and
relationships between users, advertisers and publishers
