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

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 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;

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

Operationalizing the Pocket Cube for Exact Purchasing Part II

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 continue our deep dive into the core technologies you will use with the Architecture focussed-octants.

High Complexity, High Risk, High Impact: Supply Chain Architecture

This is the most critical of all the octants — the far upper, upper right no matter which way you look at the pocket cube. These are your most critical, most complex, and most risky purchases where any interruption can be devastating, and a long term interruption could even bring the risk of bankruptcy (as you lose your key product line and/or ability to serve your customers).

While a lot of automation (and hardened AI) is used for constant monitoring, this is the category where the least automation is employed in the sourcing, contracting, supplier management, procurement, and analysis. Every decision needs to be human made and human reviewed as these are the categories where a single slip-up (or automation mistake because someone miskeyed data somewhere along the chain) can cost millions.

This isn’t to say that advanced technology isn’t extensively deployed — as it most certainly is at every single step of the process, just that the focus is on Augmented Intelligence (and making your employees super-human in their productivity and decision making prowess).

For example, best-of-breed multi-objective strategic sourcing decision optimization that can handle not only multiple providers and product options but also multiple carriers using multiple modes while balancing overall landed cost, supplier and supply chain risk, and compliance is a key requirement of RFP analysis and multi-regional dual-source award definition (as two suppliers in the same province of China that use the same port that could both be taken out by a single natural disaster, port shutdown, or local energy plant failure is NOT dual-sourcing and NOT risk mitigation).

AI might be used to pull together the first pass of the RFP, but the specs will have to be human reviewed and validated, key aspects of the response will have to be human reviewed and validated, and the award analyzed by multiple stakeholders before approval. AI can assemble a contract off of templates, but due to the complexity and risk, legal and risk management will have to carefully review that all risks that can be covered are (and mitigated to the extent possible from a legal perspective) and engineering that product/project management that the specs are complete and the obligation timeline appropriate.

Constant risk monitoring on every signal available will need to be employed, and alerts propagated on the detection of an event that could lead to an issue, not days, weeks, or months later when the issue finally materializes. (And if a human doesn’t review and respond in the system — not an issue, keep monitoring, escalate, etc., escalate the alert up the human command chain.)

  • (Strategic) Sourcing: Strategic Sourcing with Multi-Objective Optimization that balances cost, risk, compliance, and organizational objectives
  • Supplier Management: Compliance, Risk, and Performance
  • Catalog Management: Detailed product (sample) review and verification
  • Contract Management: Manually constructed off of templates, LLM and Human Reviewed to ensure all required obligations captured and risks addressed
  • Procurement (Channel)*: Goods PO (Catalog), Contract Invoice (Payment Schedule), Framework PO (Fixed Delivery Schedule), 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; Commodity markets, marketplaces, and currency exchanges;

High Complexity, High Risk, Low Impact: Cost-First Architecture

The only difference between this category and the last category is that the impact, while likely relatively significant if any disruption or issue is not resolved promptly, is not as severe (and not organizational life-threatening). It’s still a complicated category to manage due to the high complexity of the products and services, and the high risk they carry due to the supply chain or (current) market conditions, but one that you don’t need to spend nearly as much time.

You’re still doing everything at least semi-manual every step of the way, but you’re not going nearly as deep — you’re covering all the angles, but you’re not triple measuring and verifying them. You’re still using decision optimization, but it’s merely a two-factor cost vs compliance optimization. You’re reviewing the award recommendation, but you don’t need to get the stakeholders involved once you have collected their requirements. You’re verifying specs, but unless it’s a component to be integrated, you don’t have to review samples. And so on.

Also, by continually monitoring for new products and suppliers, and verifying these as they are selected, it’s pretty quick on a disruption to spin up a new event using automation that will essentially recreate the last event but send the RFP to new suppliers as well as suppliers that didn’t win last time (pre-populating with their last responses and bids to make it super easy for them to participate).

And once the key risks that have be captured in a contract are defined, and acceptable clauses created, Legal doesn’t have to review every contract (and you can handle it), and Engineering only has to get involved if a supplier is proposing a change to the spec, material composition, or obligation timeline.

  • (Strategic) Sourcing: Strategic Sourcing with Decision Optimization that balances cost and compliance
  • Supplier Management: Compliance
  • Catalog Management: Product Spec Verification
  • Contract Management: Automatically constructed off of templates, LLM and Human Reviewed to ensure all required obligations captured and risks addressed
  • Procurement (Channel)*: Goods PO (Catalog), Contract Invoice (Payment Schedule), Framework PO (Fixed Delivery Schedule), Non-PO Invoice (Emergency Replacement)
  • 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; Commodity markets, marketplaces, and currency exchanges;

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