Over the past year, a new category in the AI ecosystem has been forming quietly: networks that don’t just consume data, but coordinate the people who produce, verify, and refine it.

Most AI conversations focus on models, but anyone working close to the ground knows the harder problems live elsewhere in the supply chains that feed and validate those models. That’s where platforms like PublicAI made things tangible for me, not as an observer but as someone embedded in the loop.

What PublicAI Showed in Practice

My role with PublicAI wasn’t glamorous. On most days I was reviewing and verifying submissions as a Judge, offering feedback directly to the team, and trying to understand how real-world contributors behave, not how pitch decks assume they will.

This vantage point revealed a few key dynamics:

1. Data Quality Isn’t a Given — It’s designed

Incentives alone don’t guarantee quality. Instructions, validation, contributor education, reward structures, rejection logic, and appeal mechanisms all affect the slope of improvement. When we pushed structured feedback into the system, we saw quality rise predictably. When guidelines were unclear, rejection rates spiked and motivation dipped.

This is the part of AI most people never see.

2. Multilingual Contributors Force Better Systems

PublicAI welcomed contributors beyond the English-speaking world. Reviewing both English and Arabic submissions showed how quickly AI platforms hit friction when diversity enters the dataset. Language isn’t just translation — it brings cultural context, writing style, reasoning differences, and ambiguity in instructions.

If the future of AI is global, data pipelines cannot remain monolingual. My experience on the verification side confirmed that inclusion is not just ethical; it improves model adaptability.

3. Verification is Not Just a Filter — It’s a Feedback Market

Verification isn’t about rejecting “bad” submissions. It’s about shaping the productive boundaries of the contributor base. When feedback cycles are fast, contributors improve and the platform compounds. When cycles are slow, contributors churn. Verification becomes a system of alignment, not policing.

PublicAI leaned into that alignment, and it’s a big part of why the platform scaled without diluting standards.

A Broader Pattern: AI Needs Distributed Coordination

Zooming out, PublicAI exposed the economics of model training: centralized models rely heavily on decentralized human labor. The more contributors, verifiers, and evaluators you coordinate, the more resilient your training pipeline becomes.

That led me to a bigger realization that AI doesn’t need just better models, it needs better coordination mechanisms.

Models are already improving, shike coordination infrastructure is not and that’s what draws my attention to Perle.

Where Perle Fits in This Emerging Ecosystem

Perle approaches the problem from the complementary side: inference access, model execution, and decentralized compute distribution backed by a transparent reward system for contributors and operators.

If PublicAI focused on the “input layer” of AI (data + validation), then Perle is tackling the “execution layer” (compute + inference). These ecosystems are not competing — they are sequential.

AI needs:

1. inputs (human-generated knowledge)

2. verification (quality control)

3. compute (execution)

4. distribution (access + ownership)

We’ve spent the last decade obsessed with number three. The new wave is finally addressing one, two, and four.

Why Perle Looks Promising

A few reasons stand out:

Human Expertise Is Treated as an Asset, Not a Commodity

Perle introduces a model where expertise is verified, recognized, and rewarded instead of diluted by anonymous crowdsourcing. That increases the signal-to-noise ratio dramatically.

Onchain Attribution Builds Traceability Without Bureaucracy

Being able to point to who contributed what, when, and how without 50 layers of vendor abstraction matters for institutional adoption. Transparency is not aesthetic; it’s operational.

Quality-Weighted Rewards Fix a Major Incentive Misalignment

Platforms that pay per task tend to optimize for volume. Platforms that compensate based on demonstrated accuracy and reliability produce compounding improvement. PublicAI hinted at this Perle is institutionalizing it.

Reputation Becomes Portable

This is a big one. On most platforms, contributor reputation is trapped. Onchain reputation opens the door for multi-platform credentials, cross-platform task access, and verified contributor classes. That’s how you build an actual labor market for AI participation instead of isolated microwork pools.

Looking at Both together

PublicAI gave me firsthand exposure to how contributors behave, how verifiers gate quality, and how feedback loops shape the entire system. It made me appreciate the difference between theoretical design and lived execution.

Perle feels like the logical next phase of the same arc moving from “how do we source and verify good data?” to “how do we execute and distribute AI in a way that is transparent, auditable, and fair?”

Both point toward the same future: AI that isn’t just centralized infrastructure, but shared infrastructure. Not just centralized gain, but shared gain.

The regions that were ignored during the first wave Africa, MENA, SEA, LATAM are positioned unusually well for this one. They are contributor-rich, data-diverse, increasingly compute-aware, and motivated to participate economically, not just consume outcomes.

The next global AI platforms won’t just build better models. They’ll build better systems for the people who make those models possible and publicAI made that obvious. Perle is stepping into that future with conviction.

Recently we have many financial instrument or i will call it platforms such as prediction markets, event-based contracts, and futures trading have gained attention across crypto enthusiast in our Muslim community. These systems are often promoted as tools for forecasting, hedging, or improving market efficiency. However, for Muslims, the key question is not innovation but permissibility under Islamic jurisprudence (fiqh).

This post is written to raise awareness, encourage thoughtful discussion, and clearly explain why most contemporary Islamic scholars consider prediction markets and futures trading impermissible (haram), while also addressing the minority opinions circulating within parts of the Muslim online community.

What Are Prediction Markets?

Prediction markets are platforms where participants buy and sell positions on the outcome of future events. These events may include:

• Elections and political outcomes

• Sports results

• Economic indicators

• Policy or regulatory decisions

Participants profit if their prediction is correct and lose money if it is not. Well-known examples include:

Polymarket, Kalshi and other election betting platforms. Event-based crypto prediction protocols and similar systems

Although these platforms are sometimes framed as “information markets” or “forecasting tools,” their core mechanism remains financial gain or loss tied to uncertain future outcomes.

The Dominant Islamic Ruling: Impermissible (Haram)

Most contemporary scholars and Islamic finance bodies agree that traditional prediction markets are impermissible. This position is grounded in their resemblance to gambling (maysir/qimār) and their reliance on excessive uncertainty (gharar).

1. Zero-Sum Betting (Maysir) in a standard prediction market:

• One participant’s gain comes directly from another participant’s loss

• No tangible asset, service, or productive activity is involved

• Wealth is transferred purely based on uncertain outcomes

This aligns with the classical definition of gambling in Islamic law, where profit is earned without trade, ownership, or labor.

2. Excessive Uncertainty (Gharar)

Prediction market contracts depend entirely on future events that are:

• Unknown at the time of agreement outside the control of participants

• Not tied to a defined deliverable

Islamic commercial law requires clarity, defined subject matter, and fairness. The uncertainty involved in these contracts exceeds what is acceptable.

3. Absence of an Underlying Asset or Ownership

Unlike investing in a company where ownership, risk, and reward are clearly established a “share” in a prediction market represents a wager on a future state of the world rather than ownership of a productive asset. This further reinforces its speculative nature.

Quranic Guidance on Gambling

Allah says in the Quran:

“They ask you about wine and gambling. Say: In them is great sin and some benefit for people, but their sin is greater than their benefit.”

Surah Al-Baqarah (2:219)

Islamic jurisprudence consistently holds that potential benefit does not justify an activity when the harm outweighs it, a principle directly applicable to gambling-related systems.

Minority Discussions and Common Misunderstandings

While the dominant ruling is prohibition, some Muslim influencers, traders, and community leads publicly argue that prediction markets and futures are not haram. These views deserve examination, especially because they influence younger audiences.

1. Shallow Engagement With Islamic Rulings

Many permissive arguments:

• Focus on surface-level economic outcomes

• Rely on Western financial terminology

• Overlook foundational Islamic contract principles

In several cases, forecasting accuracy is confused with permissibility, without properly addressing maysir, gharar, or zero-sum wealth transfer.

2. Self-Interest and Incentive Bias

It must also be acknowledged that:

• Some advocates profit directly from these platforms

• Others hold tokens, partnerships, or reputational stakes

• Financial success can cloud objective legal judgment

While this does not automatically question sincerity, Islamic rulings cannot be shaped by personal benefit, popularity, or market trends. Shariah is grounded in principles, not profitability.

A. Information-Only Use (Limited and Narrow)

Some scholars accept that if a forecasting mechanism is used:

• Internally within an organization

• Without personal financial gain

• Strictly for planning or research

Then it may fall outside the definition of gambling. However, this does not apply to public, profit-driven platforms like Polymarket or Kalshi.

B. Hedging (Tahawwut) vs. Speculation

Islam distinguishes between:

• Speculation: Risk-taking for profit based on uncertainty

• Hedging (Tahawwut): Protection against an existing economic risk

While some theoretical discussions compare limited risk mitigation to takaful, this view:

• Is not widely accepted

• Requires strict cooperative structures

• Does not justify open prediction markets

Our Approach and Methodology in Sihaad Community

Before taking this position, we have spent time engaging directly with users, contributors, and discussions around prediction markets, and carefully examining how these systems function in practice. This includes understanding their technical architecture, incentive design, settlement processes, and how profits and losses are realized—both on-chain and off-chain.

Our stance is not based on fear of innovation or blind rejection of new financial tools. It is based on informed analysis and sincere effort to evaluate modern systems through established Islamic principles. Where doubt exists, Islam teaches caution, deeper inquiry, and restraint—not rushing toward permissibility for convenience or personal gain.

This has always been our approach when discussing Islamic rulings on emerging technologies: understand first, assess carefully, then take a principled position, even when that position is unpopular.

A Firm Position on Futures Trading

Beyond prediction markets, futures trading presents similar—and often greater—Shariah concerns.

Most futures contracts involve:

• Selling what one does not own

• Deferred exchange of both payment and delivery

• Profit driven primarily by price movement

These characteristics fall under:

• Maysir

• Gharar

Bay‘ al-ma‘dum (selling what is not owned or does not exist)

For this reason, we stand firmly against futures trading as permissible for Muslims, as it mirrors the same speculative behavior found in prediction markets.

Our Community Position

As a Muslim community engaging with finance, crypto, and emerging markets:

Ethical earning must take priority over trends and not every profitable system is permissible.

Innovation does not override clear Islamic principles.

Both prediction markets and futures trading, in their common forms, conflict with Islamic commercial ethics.

Fiinal ebuka's thoughts

Technology is neutral. Financial contracts are not.

Until prediction markets and futures systems are fundamentally redesigned to remove gambling-like structures, excessive uncertainty, and zero-sum wealth transfer, the Islamic ruling remains clear.

We encourage learning, sincere discussion, and consultation with qualified scholars but also caution against normalizing systems that contradict established Islamic principles.

For years, blockchain has promised to bank the unbanked. It’s a powerful slogan but in reality, the impact in emerging markets has been limited. Not because the need isn’t real, but because most solutions were built without fully understanding how fragile financial infrastructure really is in these regions.

In Sub-Saharan Africa alone, nearly half of the adult population remains unbanked. In some countries, like South Sudan, access to basic banking barely exists. Even for those with bank accounts, the systems they rely on are often unreliable, expensive, and slow. Network outages are normal. Settlements take days. Fees quietly eat into already thin margins. When things break, people fall back to cash—not by choice, but by necessity.

What struck me while reading ADI’s documentation is that they’re not pretending this problem is purely technical. They’re treating payments as national infrastructure—because that’s exactly what they are.

The Real Problem Isn’t Access It’s Reliability

Access to digital payments is growing across emerging markets, but growth doesn’t equal trust. Payment systems still suffer from frequent downtime, security breaches, and settlement delays that make them feel riskier than cash. When uptime isn’t guaranteed, digital money becomes a liability instead of a tool.

This is where many blockchain projects miss the point. A payment network that can’t guarantee reliability, compliance, and continuity simply won’t be adopted at scale—especially by governments, utilities, or large institutions.

ADI Chain approaches this differently.

Payments as Public Infrastructure

ADI Chain is built as an Ethereum Layer 2 using the ZKsync stack, but the architecture goes further. The key idea is flexibility at the regulatory level. Instead of forcing governments and institutions to adapt to a one-size-fits-all blockchain, ADI allows them to deploy their own Layer 3 networks with rules that match their compliance needs.

That matters. It means a government can maintain regulatory oversight without sacrificing speed or transparency. It means payment providers can operate within local laws while still benefiting from blockchain-level settlement times. And it means infrastructure can scale nationally, not just experimentally.

Because ADI runs on a decentralized network of nodes, the system remains functional even when parts of the network go down. This isn’t a nice-to-have—it’s critical for regions where outages are common and resilience is non-negotiable.

Faster Settlement, Lower Costs, Real Impact

Traditional payment systems in emerging markets often take three to five business days to settle. ADI Chain settles transactions in seconds, operates 24/7, and does so at extremely low cost—often fractions of a cent.

For individuals, this means sending money without worrying about timing, intermediaries, or hidden fees. For businesses, it means better cash flow and fewer operational risks. For governments and utilities, it means transparent, auditable systems that actually work at scale.

This isn’t about replacing everything overnight. It’s about offering infrastructure that’s finally aligned with how modern economies function.

Stablecoins That Fit the Region

One of the most compelling aspects of ADI’s approach is its support for regulated, regionally relevant stablecoins—starting with a Dirham-backed stablecoin regulated by the UAE central bank.

In regions where local currencies are fragmented or unstable, a trusted regional unit of account can change how people save, trade, and plan. Instead of juggling dozens of illiquid currencies, users can transact in something stable, familiar, and widely accepted—without needing access to traditional foreign exchange markets.

This is where blockchain stops being theoretical and starts being practical.

Why This Feels Different

What makes ADI stand out isn’t just the technology—it’s the framing. Payments aren’t treated as an app feature or a speculative product. They’re treated as rails: foundational systems that economies depend on.

Emerging markets don’t need more experiments. They need infrastructure that works under pressure, scales with growth, and respects regulatory realities. ADI Chain feels like it was designed with those constraints in mind.

If the future of payments in emerging economies is going to change, it won’t come from abstract promises. It will come from systems that are reliable, compliant, fast, and accessible at a national level.

ADI’s vision points in that direction a different idea of payments, built for the realities of the world most people actually live in.