China is Leading in AI!

And the real reason why? The courts are defending labour rights and NOT allowing companies to replace workers in AI.

As per a recent posting over on “The State Council Information Office (of) The People’s Republic of China” on April 30, 2026: (Source)

“A Chinese court has ruled in favor of a human employee in a labor dispute caused by AI replacement, which experts said may send a reassuring message to labor rights protection efforts in the age of automation.”

Furthermore, this was not the first time!

On December 26, 2025, the Beijing Municipal Bureau of Human Resources and Social Security released a set of arbitration cases for 2025, including a dispute triggered by AI-driven job displacement. In that case, the arbitration panel made it clear that 𝐀𝐈 𝐫𝐞𝐩𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 𝐝𝐨𝐞𝐬 𝐧𝐨𝐭 𝐯𝐚𝐥𝐢𝐝𝐚𝐭𝐞 𝐚 𝐝𝐢𝐬𝐦𝐢𝐬𝐬𝐚𝐥. It found that adoption of AI technology is a voluntary move to stay competitive and not one that is mandated or acceptable as a basis for human replacement and dismissal.

Furthermore, legal scholars in China are emphasizing that 𝐭𝐡𝐞 𝐜𝐨𝐬𝐭𝐬 𝐨𝐟 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐬𝐡𝐨𝐮𝐥𝐝 𝐧𝐨𝐭 𝐛𝐞 𝐛𝐨𝐫𝐧𝐞 𝐬𝐨𝐥𝐞𝐥𝐲 𝐛𝐲 𝐰𝐨𝐫𝐤𝐞𝐫𝐬 and that while 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐩𝐫𝐨𝐠𝐫𝐞𝐬𝐬 𝐦𝐚𝐲 𝐛𝐞 𝐢𝐫𝐫𝐞𝐯𝐞𝐫𝐬𝐢𝐛𝐥𝐞, 𝐛𝐮𝐭 𝐢𝐭 𝐜𝐚𝐧𝐧𝐨𝐭 𝐞𝐱𝐢𝐬𝐭 𝐨𝐮𝐭𝐬𝐢𝐝𝐞 𝐚 𝐥𝐞𝐠𝐚𝐥 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤.

This is the thinking that will allow for actual progress and development.

AI is not intelligent, humans are still needed, and progress will be made when we stop accepting the BS that AI can replace us and instead only listen to and work with companies that state that appropriately designed, implemented, and/or restricted AI can augment us in our jobs and make us 3, 5, and even 10 times more effective — enabling us to be super human workers.

It might be too late for the US, but if Chinese courts continue to make rulings that indicate that 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐰𝐡𝐨 𝐛𝐞𝐧𝐞𝐟𝐢𝐭 𝐟𝐫𝐨𝐦 𝐀𝐈-𝐝𝐫𝐢𝐯𝐞𝐧 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐠𝐚𝐢𝐧𝐬 𝐦𝐮𝐬𝐭 𝐛𝐞𝐚𝐫 𝐜𝐨𝐫𝐫𝐞𝐬𝐩𝐨𝐧𝐝𝐢𝐧𝐠 𝐬𝐨𝐜𝐢𝐚𝐥 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬, it won’t belong before China is truly dominating the world (since the US will have no competent employees left when everything goes to hell).

Ontologies Could Have Saved Us — But in the Age of Gen AI, They Might Just Ruin Us!

What is an Ontology?

Philosophically, an ontology is the study of being, existence, and/or reality that is designed to investigate not only what entities exist but how they can be categorized.

In computer science and, more specifically, the data age, an ontology is a formal, machine readable, specification of entities, their properties, and their relationships within a domain that is used to structure information in a way that systems can share and structure it.

In the early days of semantic technology, an ontology was used to structure data in a meaningful way to allow sophisticated models to process, and make sense of, natural language with relatively high degrees of accuracy. It was usually expressed in a formal ontology language that allowed for detailed entity, relationship, part of speech, and even concept definitions. They were often defined in such a way they could be organized into interconnected libraries which formally organized knowledge into large, connected, corpuses that could be deterministically processed (hallucination free) and completely understood by any application that was capable of processing the language the ontologies in the library were encoded in.

And this was the true beginning of the semantic web, which was also known as Web 3.0, which was still in its infancy in the 2010s, but starting to take off by early (early) adopters (with almost 2% of web domains containing semantic markup circa 2014).

But then five things happened.

1. SaaS exploded, and so did the need for data, and the ability to consume it in standard formats.

2. GPT-1 was released in 2018 and the Gen-AI craze began shortly thereafter, leading us down the hallucinatory hole of incessant inanity that every consultant thought could power everything.

3. This led to the agentic craze, which increased the demand for data (and the desire to consume it in structured formats).

4. Every SaaS provider, and their dog all of a sudden needed multiple, steady, streams of data in standard formats to power their agentic applications.

5. In response, every data provider responded by adopting a simple data standard, calling it an ontology, even if all they were serving up was average scope 3 carbon data by country and factory type.

And now the term has no meaning since it’s the term used by every SaaS vendor and data supplier to essentially describe their data file structure. No formality. No relationships. No underlying structure that allows the machine to actually reason. Just another random data file blended into the data soup that feeds the hallucinatory engine that will tell us to go over the cliff like lemmings (and lead countless to their deaths as they cognitively surrender to what the AI tells them to do).

What could have been our saving grace (if Web 3.0 research had continued and true ontologies of ontologies had been created) might soon be the source of our demise as Gen-AI blends together mismatched data with flawed reasoning and produces the digital equivalent of toxic waste.

In two weeks — ALL YOUR DATA BELONGS TO MUSK, ZUCKERBERG, NADELLA, and ALTMAN!

Not being facetious here! It could be step 1 in Musk’s plan to own all your data!

A ruling in two weeks could ultimately result in ALL YOUR DATA BELONGING TO MUSK, ZUCKERBERG, NADELLA, and ALTMAN!

In only two weeks, Texas Third Court of Appeals has a hearing on an emergency motion by Alex Jones’ lawyers that temporarily blocked the transfer of any Infowars assets. (Which were supposed to be transferred and sold to pay off the more than US$1 billion in defamation lawsuit judgments for the relatives of the victims of the 2012 Sandy Hook Elementary School shooting.)

Now, whether or not you agree with that judgement or not or the sale or not, that’s not important. What’s important is that on October 14, 2024, LATHAM & WATKINS LLP, on behalf of X Corp., filed a “Notice of Appearance and Demand for Service of Papers” relating to the case and then, on November 25, 2024, filed a statement on “X CORP.’S LIMITED OBJECTION TO TRUSTEE’S PROPOSED SALE MOTIONS”.

Now if you think this has anything to do with Musk trying to protect Jones, Infowars, or its assets, you’re wrong.

Let’s take paragraphs 1, 2, 3, 4, 25, 26, and 36.

1: Objects to the sale of any account on the “X” platform.

2: Specifically, Infowars, Banned.Video, WarRoomShow, RealAlexJones, and any other account on X belonging to FSS or Jones

3: because accounts on X are X. Corp’s exclusive property

4: and X-Corp is the sole owner

25: and has ultimate control over the accounts.

26: While section 3 of the X Terms of Service (TOS) makes clear the account holder owns the content, section 4 gives X Corp broad rights to “access, read, preserve, and disclose any information”.

36: In addition to being a personal license, the license X Corp. grants to account holders
is an intellectual property license.

Getting the picture? Probably not. Let me spell it out.

An account belongs to the person or an authorized person from a legal entity that creates the account (and, in the latter case, can only be transferred to another person from that legal entity) and cannot be transferred to anyone else under those terms of services.

As a person, you can only access the account as long as you personally are mentally and physically capable of doing so and do not violate the terms of service. As a legal entity, as long as you remain a valid legal entity and have a valid designate to do so.

When these conditions cease to be met, your access is denied, and your account eventually shut down, but X Corp. retains the right to preserve, access, and read that data for eternity, while your (or anyone else’s) rights to such data effectively expire (unless you preserved a copy of such data off of the platform, and transferred your copyright to another entity before you died) as you no longer have a copy or the ability to prove copyright. That data then effectively becomes property of X Corp.

And this is Musk’s effort to have a Judge state that this is legally correct. Because, like its peers, xAI used every available bit of data on the internet to train its models, including every copyrighted book, song and movie/tv show in digital format they could access. And, like his peers, Musk doesn’t want his company sued. (And that’s the real reason there is a 10-year moratorium on AI regulation. It’s not to catch up to China. It’s not to ensure the government has the ability to experiment without recourse in civilian monitoring, military, and electioneering efforts. It’s so the politicians don’t lose access to the biggest money pots out there.)

This is the first step. Have a judge say that social media platforms (where internet users spend most of their time and post most of their data) legally own the service, which is defined as non-transferable in the TOS which also allows the platform to retain all data posted indefinitely. Have the the only copy of the data when the service is abandoned or terminated and assume the rights by default. Then you can’t be sued because you now own the data (because you will by the time the no AI regulations moratorium expires and laws actually get passed).

Sources:

1) CP24.com

2) KUT.org

3) Demand for Service of Papers

4) LIMITED OBJECTION TO TRUSTEE’S PROPOSED SALE MOTIONS

Operationalizing the Pocket Cube for Exact Purchasing Part IV

A few weeks ago, we not only told you that Exact Purchasing is a Pocket Cube, but we broke it down and defined each octant for you, as well as indicating which categories of goods and services were most likely to fall in each octant (with the disclaimer that there is variation between industry and sometimes even companies in the same industry based on size and focus).

This was a great start, but once you understand the breakdown, the next step is understanding how you go about sourcing and procuring the categories in each octant. Today we conclude our deep dive into the core technologies you will use with the Governance focussed-octants.

High Complexity, Low Risk, Low Impact: Spend Governance

Low risk and low impact means it’s almost a prime category for automation, except that high-complexity requires a fair amount of human oversight as not just any product from a catalog (or any service from a random service provider) will do. However, as long as humans are in the loop to approve the providers and the products, this is another category where a lot of automation can be employed, especially if the right technology is available.

This is another category where decision optimization needs to be employed as part of the strategic sourcing process, where continual compliance (as well as risk) monitoring needs to be employed as well as manual verifications of all suppliers and products before they enter the autonomous sourcing process and of all specs and obligation requirements before the contract is inked.

(Strategic) Sourcing: Autonomous Strategic Sourcing with Decision Optimization that balances cost and compliance
Supplier Management: APLs and Compliance Monitoring
Catalog Management: AVLs
Contract Management: Auto-Creation, Human Review of Specs and Obligations, Auto-Sign
Procurement (Channel)^*: Goods PO (Catalog), Framework PO, Consignment PO, Service PO
Monitoring: ACK, ASN, Receipt in the Procurement System; Lead Time, Delivery, Quality Trends in the Inventory Management and Production Systems;

High Complexity, Low Risk, High Impact: Relationship Governance

High complexity and high impact is tough. Not as tough as when risk is also high, and you need full supply chain architecture that you’re manually sweating through every step of the way, but tough enough because while shipments will mostly be assured, if they aren’t up to spec, that’s just as bad as a missed shipment.

This is another category where sourcing can only be semi-autonomous as you need to verify the model, employ multi objective decision optimization and award review, review the specification, obligation, and risk management aspects of the contract in detail, and monitor the compliance, quality, and timeliness of the delivery. And monitor the compliance continuously.

(Strategic) Sourcing: Semi-Autonomous Strategic Sourcing with Decision Optimization that balances cost and compliance with Award Analysis and Review
Supplier Management: APLs, Compliance and Performance Monitoring
Catalog Management: AVLs and regular review and approval of new product options and regular automatic identification of potential products for review
Contract Management: Auto-Creation, Human Review of Specs and Obligations, Auto-Sign
Procurement (Channel)^*: Goods PO (Catalog), Framework PO, Consignment PO, Service PO
Monitoring: ACK, ASN, Receipt in the Procurement System; Lead Time, Delivery, Quality Trends in the Inventory Management and Production Systems; Financial Status, Litigation Monitoring, Sanction Monitoring, News, Event, and Sentiment Monitoring;

This concludes our initial series on operationalizing the pocket cube of Exact Purchasing!

^* Unless the Channel-Master Joël Collin-Demers says otherwise.

Operationalizing the Pocket Cube for Exact Purchasing Part III

This was a great start, but once you understand the breakdown, the next step is understanding how you go about sourcing and procuring the categories in each octant. Today we continue our deep dive into the core technologies you will use with the Risk (Monitoring) focussed-octants.

Low Complexity, High Risk, Low Impact: Continuous Market Monitoring

If it wasn’t for the high risk, this would be a transaction category. As a result, this is one of the categories that is heavily automated. In fact, the only human intervention that is needed is human review and approval of suppliers and products (and organizational requirements). Once these are defined, autonomous systems can be set up to completely manage the (re) sourcing process.

The main difference between this category and the transaction category is the extent of signals that need to be monitored to detect, and respond, to risk (related) events in (near) real time and ensure the supply chains keep supplying on time. The monitoring has to cross Procurement, Inventory, ERP, and External (News and Event and Financial) (Data Feed) systems and keep tabs on all relevant signals so that any relevant signal is captured and automatically responded to.

(Strategic) Sourcing: Autonomous Dual (Region) Sourcing with Near-Equal Splits
Supplier Management: AVLs with strong Compliance and Risk Management
Catalog Management: APLs
Contract Management: Auto-Creation and Auto-Sign
Procurement (Channel)^*: Goods PO (Item Master), Framework PO (Fixed Delivery Schedule), Non-PO Invoice (Emergency Replacement), PCard (Seasonal Purchase)
Monitoring: ACK, ASN, Receipt in the Procurement System; Lead Time, Delivery, Quality Trends in the Inventory Management and Production Systems; Sanction Monitoring, News and Event Monitoring;

Low Complexity, High Risk, High Impact: Market Risk Management

This category isn’t just high risk, but high impact. As a result, while this is one of the categories that you want to heavily automate due to low complexity, it’s a balance between automation and human intervention. Unlike our last category, additional intervention is required before award and upon every significant alert, to see if a relationship, market, mitigation, or re-sourcing/re-purchasing action is needed.

The main difference between this category and our previous continuous market monitoring category is that the high impact nature of this category means that simply re-sourcing is not enough of a risk management strategy and mitigation options need to be pre-defined so they can be quickly executed if a risk is detected.

(Strategic) Sourcing: Semi-Autonomous Dual (Region) Sourcing with Near-Equal Splits, Human Award Analysis and Review
Supplier Management: APLs and Performance Monitoring
Catalog Management: AVLs and regular review and approval of new product options and regular automatic identification of potential products for review
Contract Management: Auto-Creation, Human Review of Obligation and Risk Mitigation Clauses, Auto-Sign
Procurement (Channel)^*: Goods PO (Catalog), Framework PO (Fixed Delivery Schedule), Non-PO Invoice (Emergency Replacement), Consignment PO (VMI)
Monitoring: ACK, ASN, Receipt in the Procurement System; Lead Time, Delivery, Quality Trends in the Inventory Management and Production Systems; Financial Status, Litigation Monitoring, Sanction Monitoring, News, Event, and Sentiment Monitoring;