Dark Factories, Large Corp. Brands, Super-AI: Fully Automated Appraisal

[RCA]

The world is changing fast.

1. I surprised to see a YouTube interview of an Indonesian clothing manufacturer complaining in hopelessness of them trying to compete with new Chinese "Dark Factories" which can produce clothing at a much lower cost than they in Indonesia (lower educational standards). The Chinese factories have completely automated the process of manufacturing clothing with 100% automated dark factories that operate 24/7.
COUNTERPOINT: We can do the same in the US.

2. 24/7 100% automated factories are the future!

3. Then I asked X.AI/Grok: How long do you think it will take to completely automate the task of appraising residential homes?

SuperGrok: "The complete automation of residential home appraisal—encompassing data collection, analysis, physical inspection, and final valuation without any human intervention—is a complex challenge that depends on advancements in technology, regulatory acceptance, and market dynamics. Based on current trends and barriers, I estimate it could take 15 to 25 years (by roughly 2040–2050) to achieve near-complete automation, though partial automation will continue to advance rapidly in the interim. Below, I’ll break down the factors influencing this timeline, the current state of the field, and key hurdles to full automation.

Current State of Home Appraisal Automation​

Residential appraisals involve assessing a property’s market value based on its location, condition, features, and comparable sales. Automation has already made significant inroads:

• Automated Valuation Models (AVMs): Tools like Zillow’s Zestimate, Redfin’s Estimate, or CoreLogic’s models use algorithms to analyze public data (e.g., sales records, tax assessments, square footage) and generate valuations. These are widely used for preliminary estimates, with accuracy often within 5–10% of professional appraisals for standard homes.
• Data Aggregation: Platforms like Black Knight and ATTOM Data Solutions compile extensive property data, including historical sales, permits, and neighborhood trends, reducing manual research.
• Digital Tools for Appraisers: Software like Total or a la mode streamlines report generation, and geographic information systems (GIS) aid in analyzing location-based factors.
• Emerging Technologies: Drones and satellite imagery are starting to assist with exterior inspections, while AI-powered image recognition can estimate property conditions from photos (e.g., Roofstock’s tools for rental properties).

However, human appraisers remain essential for subjective tasks like interior inspections, assessing unique property features (e.g., custom renovations), and applying judgment to nuanced market conditions.

Factors Influencing Full Automation​

To estimate the timeline for complete automation, several technical, regulatory, and practical factors must be considered:

1. Technological Advancements (5–15 Years for Maturity)
   • Data Integration: Comprehensive automation requires integrating disparate data sources—public records, real-time market trends, and hyper-local factors (e.g., school quality, crime rates). Current systems are robust but lack granularity for unique properties. Unified, high-quality datasets could take 5–10 years to standardize globally.
   • AI and Machine Learning: AI models must improve in handling outliers (e.g., historic homes, distressed properties) and predicting market sentiment, which fluctuates based on economic conditions. Current AVMs struggle with non-standard homes, with error rates rising to 20–30% in such cases. Achieving human-level accuracy across all property types could take 10–15 years as deep learning and natural language processing evolve.
   • Physical Inspections: Interior and exterior inspections are a bottleneck. Drones and 360-degree cameras can handle exteriors, but assessing interior conditions (e.g., wear and tear, upgrades) requires advanced robotics or homeowner-submitted data. Autonomous inspection robots with computer vision (e.g., Boston Dynamics’ Spot adapted for homes) are in early stages and may need 15–20 years to become cost-effective and reliable for widespread use.
   • Digital Twins: Creating real-time digital models of homes, combining IoT sensors (e.g., smart home devices) and 3D mapping, could streamline appraisals. This tech is nascent and likely 10–15 years from mainstream adoption in residential settings.
2. Regulatory and Industry Acceptance (10–20 Years)
   • Appraisal Standards: In the U.S., the Uniform Standards of Professional Appraisal Practice (USPAP) govern appraisals, requiring human judgment for federally backed loans (e.g., Fannie Mae, Freddie Mac). Shifting to fully automated systems would need regulatory overhaul, as lenders prioritize reliability and accountability. Pilot programs for AVMs in low-risk loans are underway (e.g., Freddie Mac’s ACE program), but scaling to all appraisals could take 10–15 years due to caution around bias and errors.
   • Bias Mitigation: Automated systems can perpetuate biases (e.g., undervaluing minority-owned properties) if trained on flawed data. Addressing this through transparent, audited algorithms will delay adoption as regulators demand fairness, potentially adding 5–10 years to ensure compliance.
   • Licensing and Liability: Appraisers are licensed professionals liable for errors. Transferring this responsibility to AI systems raises legal questions (e.g., who’s accountable for a bad valuation?). Resolving these could take 15–20 years as legal frameworks catch up.
3. Market and Economic Factors (Ongoing Influence)
   • Cost-Benefit Tradeoff: Human appraisals cost $300–$600 per home, while AVMs are cheaper but less trusted for high-stakes transactions. Developing fully automated systems (e.g., robots + AI) must become cost-competitive, which may take 15–20 years as hardware and software costs decline.
   • Consumer Trust: Homebuyers, sellers, and lenders often prefer human oversight for major investments. Building confidence in fully automated appraisals, especially for unique or high-value properties, could lag behind tech readiness by 5–10 years.
   • Market Variability: Real estate markets differ widely (urban vs. rural, luxury vs. starter homes). Automation must adapt to diverse conditions, delaying universal adoption until systems can handle edge cases reliably, likely 15–25 years for full coverage.

Timeline Breakdown​

• Short Term (0–5 Years, by 2030): Enhanced AVMs dominate preliminary valuations, with 80–90% accuracy for standard homes. Drones and homeowner-submitted videos/photos reduce exterior inspection needs. Human appraisers focus on complex cases.
• Medium Term (5–15 Years, by 2040): AI models achieve near-human accuracy (95%+) for most properties, integrating real-time data like IoT sensor feeds. Regulatory changes allow automated appraisals for low-risk loans. Basic inspection robots handle exteriors and simple interiors, but humans oversee unique properties.
• Long Term (15–25 Years, by 2050): Fully autonomous systems—combining advanced robotics, digital twins, and AI—conduct end-to-end appraisals, including interior inspections via home-installed sensors or mobile robots. Regulatory frameworks and consumer trust align, enabling lights-out appraisal processes for nearly all homes, with humans relegated to rare oversight roles.

Key Hurdles to Full Automation​

• Subjectivity: Valuing unique features (e.g., a custom kitchen’s appeal) requires contextual judgment AI struggles to replicate. Human-like reasoning may take decades to perfect.
• Access Barriers: Interior inspections need homeowner cooperation or universal smart-home tech, which faces adoption hurdles, especially in older or rural properties.
• Economic Resistance: Appraisers’ unions and industry groups may resist job displacement, slowing regulatory shifts. In 2023, the U.S. had ~80,000 appraisers; automation threatens this workforce, prompting pushback.
• Edge Cases: Rural areas with sparse data or historic homes with no comparables challenge algorithms, requiring hybrid approaches longer than urban markets.

Conclusion​

While partial automation of home appraisals is already here and will expand rapidly, achieving complete automation—covering data analysis, physical inspections, and final valuations with no human input—will likely take 15–25 years due to technological, regulatory, and market complexities. By 2040–2050, advancements in AI, robotics, and digital infrastructure could make this feasible, but subjectivity and trust issues may keep humans in the loop for edge cases even then. If you’d like, I can dive deeper into a specific aspect, like AI’s role or regulatory trends, or explore related topics like automated valuations in other countries. Let me know what interests you!"

 

[RCA]

Dark Factories; Further links:

America Behind in Dark Factories:

Tesla Dark Factories:

Chinese Dark Factory Robots (Guandong, China)

https://www.youtube.com/shorts/isfRd5tfstY

https://www.youtube.com/shorts/POq0YWtGyL8

https://www.youtube.com/shorts/HqURxSmb0lY

https://www.youtube.com/shorts/Z2HwRrrNQ1w

MES: Manufacturing Execution Systems

https://www.gefasoft.de/en/guidelines-mes/mes-for-industry-4-0/

Amazon.com

..... Just go to YouTube and search for "dark factories"

Costco Kirkland often better than "Name Brand" quality:
https://www.youtube.com/watch?v=042pDj9FJ7Y

 

[RCA]

1. The overall picture is that 100% automation, factories and services that run 24/7 are the future. Costs will be low. Quality will be virtually perfect. Most people will be paid some bi-weekly wage, details to be worked out, even if they do have jobs or career skills. Pay may be adjusted for educational and/or skill qualifications, if they have potential to provide usuable services.

2. Most goods will be produced by massive factories, run by automation. Human jobs in these large corporation environments will be focused on the edge: Management, design, engineering, sales.

3. Niche markets, with limited distribution, will likely be handled by small to medium size companies. This will provide some opportunities for startups. It is a competitive world and many entrepreneurs will be looking to give their customers an edge in competing for business. There will be some opportunity.

4. Costco "Kirkland" like brands will dominate most mass consumed product: Low-cost w/high-quality.

 

[Elliott]

They seem to have problems with stairs and walking around, something appraisers are superb at. : )

 

[RCA]

In light of the above, especially after getting into the details, current Appraisal leadership is far behind the curve. They only scratch at the superficial surface of an industry that is moving across all sectors at a rather fast speed.

1. If you have some intelligence, you might rather consider studying MES (Manufacturing Execution Systems) and getting into robotics, rather than doing appraisals.
2. I am leaving traditional appraisal myself, because it is dying or already dead. And, there is absolutely no way current leadership can adapt to the future anytime soon.
3. If you look at most of the current so-called "leading-edge" technical development in appraisal, at least that is recognized by the established appraisal industry, it is still entrenched in the past.

4. Traditional appraisers will be replaced by valuation or financial engineers, developing algorithms, software and various types of robotic devices for inspection.
5. Entire counties, states and even countries, will be valued en-masse on a constant basis - and people who need valuations will just go online and order them.
6. That is to say: There will be a Dark Factory for valuations, running 24/7: Houses, cars, airplanes, office buildings, robots (buying/selling new/used), ....

 

[Red Flint]

I am leaving traditional appraisal myself, because it is dying or already dead.

Oh, I think there is more fun to be had. Take two residential assignments, apply Mars/R to one, and apply the technique your peer appraiser down the street would use for the other. Evaluate modeling time and severely critique the benefits versus results in light of intended user and use. Repeat, repeat, repeat. Do not forget competitive fee range. You have the parts and smarts to gather more data on your modeling accomplishment versus the competition, and the site visit representative will be no wiser. As mentioned before, also a key time to provide leadership and mentorship to those younger traveling along the curve. Good luck.

 

[RCA]

Oh, I think there is more fun to be had. Take two residential assignments, apply Mars/R to one, and apply the technique your peer appraiser down the street would use for the other. Evaluate modeling time and severely critique the benefits versus results in light of intended user and use. Repeat, repeat, repeat. Do not forget competitive fee range. You have the parts and smarts to gather more data on your modeling accomplishment versus the competition, and the site visit representative will be no wiser. As mentioned before, also a key time to provide leadership and mentorship to those younger traveling along the curve. Good luck.

I have often thought of this.

1. You could use a GitHub repository to record the predictions and results, tracking running averages. I mean as competition. Everything in GitHub is timestamped, all changes are timestamped.

2. But it is one thing to guess a sale price and another to provide the reasoning. You have to provide reasoning, You will be forced to do everything via feature value contributions. You will have to show you really know what you are doing. Otherwise, the results of your method might be accurate in specific cases only because of random chance.

3. Honestly the "peer method" is usually not going to do good if we use complex neighborhoods, homes more than 30+ years old.

4. Also, you need to describe your adjustments. Subjective adjustments made without objective and mathematically perfect constraints are categorically open to attack: If your justification is based only on your experience and doesn't have any math constraints, the other party can simply say what if his subjective opinion is 20-30% higher than yours. What are you going to do about that?

5. In the end, only advanced appraisers will compete. Traditional or so-called "peer" appraisers, can't even provide value contributions, - only adjustments which can be easily attacked in complex neighborhoods. I can demolish a "peer" appraisal - in a complex, heterogeneous area - no time flat.

 

[OSU Beavers]

With all of the incompetent Assessors, plus lying Builders and Realtors listing different house and site sizes I spend a great deal of my time vetting and correcting comparable information. Brag about AI or AVMs all you want, but it is still Garbage in = Garbage out.

 

[Digger88]

Over time an acceptable amount of automation will be allowed to take place but guarantee there will be laws in the future to prevent total domination the government still needs workers to pay taxes

 

[RCA]

Over time an acceptable amount of automation will be allowed to take place but guarantee there will be laws in the future to prevent total domination the government still needs workers to pay taxes

Oh, the Robots will be taxed at high rates. They don't need to eat much, mostly repair I suppose. 1 Robot can replace 3 workers, simply because it can work 3 shifts of 8 hours each, saving a company on average probably at least $300K/year from that alone.. Consider too they will be in many cases far more productive than people. The robots made by other robots will eventually become relatively cheap, costing maybe $100K max, lasting hopefully 5-10+ years, with some maintenance and repair costs.

So, it's intuitive, companies can and will pay hefty taxes on their robots.

And so:

1. Companies buy robots from manufacturers and also pay US/State Gov taxes on robots to finance the infrastructure and provide citizens with income to survive and maybe flourish.

2. In turn, the US Government pays citizens wages based on education/skills to stay home when they have no use for them.

3. Citizens take the money and buy manufactured goods.

4. And around it goes.

Probably the citizens get a good deal, because if they are not happy, they have plenty of time to descend on state capitals and Washington DC to protest the government math. Although, of course, the government controls the military and police, which can work both ways. But, the robot companies can provide all the police robots the government needs to do their bidding. - Hard to say how it will work out in the end.