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Explainable AI is essential from an ethical point of view because its success determines that of products and services like those offered by zillow realtor.
Zillow Offers Team's Director of Applied Sciences spoke to CISIN about why and how XAI were such integral company members. When joining four years ago, Zillow was working on its "Zestimate," an estimated product used to calculate home values.
Early 2014 saw crowdsourced assistance for home valuation by recruiting three data scientists that improved Zestimate by 13% each. As the Director stated: The goal is giving people more power in making better decisions for their homes". "This problem appealed to me not just due to being an interesting machine learning challenge but rather because giving people more power so people make more informed decisions."
We became fascinated by its "Zestimate," an estimation product used mainly by people like myself that estimate home values.
Experts said "to give people more power to make better decisions when improving the Zestimate algorithm by 13% each." Experts said "this goal of giving people more power so people make better decisions regarding their homes." This goal of giving people power, making better decisions regarding home purchases."
Zillow Offers introduced approximately 18 months ago, which further intrigued him. "Zestimate helped change how people shopped by providing clarity into previously opaque spaces; now we want to move deeper in transaction processes to change people's ways," stated its Director.
Zillow Offers, though relatively young, has seen rapid expansion. Launched first in Phoenix, Arizona, back in April 2018 before expanding to 22 other cities, including Los Angeles, by September 2020; five more markets should be added by the middle of 2024.
Over 80,000 homeowners requested an offer with Zillow in Q3 2019, yet its conversion rate remained lower, purchasing 2,2991 houses but selling 1,211. That means almost half of its purchases from Q3 remain active compared to purchases during other quarters.
Zillow presents numerous challenges. According to experts, its focus should be reducing home sellers' stress. This is especially pertinent if their motivation for selling was caused by an emotional event such as death or job relocation.
The process can be complex.
Why Explainable AI Is Important
Would you trust a physician who recommended treatment but could not explain the reasoning for their recommendation? Likewise, trusting AI systems requires being comfortable with its recommendations if trustworthiness and comfortability are to be maintained.
Explainable AI refers to methods and processes enabling human users to comprehend and challenge results generated by machine learning algorithms, giving them greater trust in how AI processes data-crunching activities. Explainable AI helps ensure humans stay comfortable using this type of artificial intelligence technology for data crunching activities, as their basis is clear.
Imagine that a bank was making predictions regarding the likelihood of credit card customers defaulting. Should these odds increase significantly, customer management staff might be alerted to review further or contact clients as necessary.
An AI platform should offer customers an explanation for its predictions. Customers require this explanation to understand why their data has been flagged for investigation by the company and take appropriate actions as per these calculations and data sets human experts may occasionally exercise their judgment override models too.
Predictions should always be evaluated against their purpose and what the AI model intends to use, taking care to consider key considerations before acting upon predictions made by AI models.
Failure to assess these vital points would be irresponsible and financially hazardous; rather than risk unthinkingly accepting results without further evaluation or due diligence checks, it is responsible and prudent to critically appraise predictions before accepting their outcome as reality.
As data evolves and becomes outdated, predictive models require constant review to maintain accuracy in their predictions.
Data drift can compromise accuracy over time. AI models derived from data may contain unintentional biases, which lead to false predictions. Google issued an apology in 2017 after their Natural Language Processing (NLP) based analysis tool assigned negative sentiment scores to words related to gayness and homosexuality while providing neutral scores for straight individuals.
Regulations Scrutiny
AI provides for responsible data usage, helping companies meet increasing corporate responsibility and regulatory demands surrounding AI technology.
For instance, The General Data Protection Regulation of the European Union (GDPR) mandates ethical behavior when using artificial intelligence; violations can lead to stiff fines.
By 2024, at least 20 U.S. states will consider artificial intelligence-related legislation or resolutions; some could become law in Alabama, Colorado, Illinois, and Mississippi.
As AI becomes incorporated more fully into operations, expect increased regulation that requires organizations to explain what goes on behind their models.
Data visualization and explanation are solutions to making AI more trustworthy and responsible. Data visualization allows information to be presented visually for easier comprehension; it makes identifying patterns and trends within datasets much simpler, making no-code AI an increasingly attractive solution with its no-code platform providing these features while offering scale capability.
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Offer Accuracy: A Challenge
Selling and purchasing homes can be exhausting and difficult, with inspections on both ends being required, repairs needed for both, renovations required for both, and timing an important factor.
You could end up in an awkward "chicken and egg" scenario if your goal is to use profits from one sale as a downpayment on another; you would then need to place offers before anyone else and then wait to sell what you own to complete this transaction; in doing this, you risk ending up with two mortgage payments, one for your current one and one for one more. Zillow acts as an intermediary, alleviating this dilemma and offering cash prices within days without waiting for offers, scheduling inspections, making necessary repairs yourself, or accepting higher offers from buyers.
Zillow Offers' main challenge lies in assessing the value of an offer. Housing prices can be difficult to anticipate and differ widely depending on several variables like region, state, neighborhood, and even street location.
Zillow provides its pricing using "comps," which compare properties similar to one another; however, there may still be subjectivity when considering features like the size of the yard or brand-new kitchen availability. Housing prices can be affected by multiple interdependent variables that influence each other, many of which have subjective importance and value.
Humans In The Loop
Zillow is an immensely data rich organization. Their website gives them insight into what types of information people want.
Zillow Offers stands out because we are purchasing and helping transact a home not simply posting numbers online as part of shopping aid; this time, we are purchasing one for around $300,000. "That makes this transaction much higher stakes" Expert said. Zillow Offers is an intelligent platform powered by their in-house analysts and local partners such as realtors.
Their AI tools combine human knowledge and judgment with AI for optimal results, forming a "human in the loop" model.
Humans and machines often struggle to communicate efficiently, which makes collaboration challenging. Each industry has its own vocabulary, terminology, and processes, which must be translated for models to perform similar assessments on identical factors for comparative analyses.
Housing is no exception here, either. Each has its terminology, which must first be communicated between humans and machines before any comparison analyses can occur.
Immediate recognition of XAI's importance becomes obvious almost instantly. Experts stressed the significance of including humans in any system to enhance accuracy; humans can help audit and validate data more readily than machines alone and produce optimal output from both sources.
An expert recently presented a deep learning technique known as "This Looks Similar To That." Known as ProtoPNet (prototypical part net), this network architecture dissects an image by finding prototypical components before combining evidence for classification producing so-called prototype images, which experts described as being separated apart into components with each prototype providing evidence towards classification, with its output consisting of summarized prototype images like Zillow Offers uses similar home sales as examples of prototype images (prototypes).
Experts further explained that Zillow Offers uses similar home sales as models' "prototypical."
Experts agree: this technique uses an industry driven definition of explainability to ensure consistent application.
Zillow Offers' human-in-the-loop system or any human/machine interface system for that matter faces the difficulty of striking the perfect balance between machines and people in its functioning. According to experts, one needs to identify when humans and machines should work together effectively to optimize it further.
A Science And An Art
Experts refer to this process as both science and art: it relies heavily on local agents with extensive knowledge of an area who can tell if a neighborhood is flourishing or street noise levels near homes are excessive compared to machine learning's "science." This interaction between experts and local agents has often been described as the difference between machine learning being "art" vs.
"science."
Human auditors of data provide intangible, qualitative feedback. They can spot obvious data errors for instance, if the square footage listed is substantially off from county records by checking photos and comparing with county records; they can label data unavailable at scale and take closer looks to assess potential repairs or verify past renovation work quality.
Reports or photos may fail to reveal certain things; photos can mislead and mask problems. What might seem ideal from photos may turn out differently when entering a home for instance, if its floor tilted when computer vision would likely miss such errors.
Human auditors can greatly enhance accuracy by recognizing errors and improving data input into the system. A great example would be flagging issues with slanted flooring; once identified by humans and noted on paper by model-run estimates, that information could then be added back in and surfaced when the next house goes for sale.
Experts agree that merging human art with machine science through language translation could take things to the "next level".
Comparison: Redfin, Zillow, And Realtor.Com
What Is Redfin?
As an innovative brokerage service platform, Redfin offers lower commission rates than conventional realtors, thus enabling homebuyers and sellers alike to save thousands in commission fees when conducting real estate transactions using this method.
Redfin agents offer cash rebates to property owners for using their service while providing support for sale by owner (FSBO) listings at Fizber and FSBO websites which appear within 48 hours.
What Is Zillow?
Zillow, an online marketplace for real estate listings, works differently from Redfin. They allow FSBO listings (for sale-by-owner), where sellers can upload their property directly onto the market to save agent fees and commission.
36 Million Unique Visitors visited this platform monthly (U.S.).
What Is Realtor.com?
Realtor.com has quickly become one of the most accurate platforms for real estate listings online today. As part of over 580 MLS databases that regularly receive updates across America, in zillow vs realtor, realtor features greater regional coverage than Redfin or Zillow due to being established in 1996 (while Redfin was launched in early 2000 and Zillow shortly after in 2002).
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How Do Online Property Estimators Work?
Real estate listing platforms allow users to estimate the value of their home using home value estimators tools online, giving an approximate assessment.
Home Value estimators offer many advantages, including:
- Agents can better understand average property prices in the area.
- Find properties within your budget to help you find the best property for you.
- Refinancing Options for Homeowners More Information.
Estimates that take place online often raise disputes about their accuracy and validity, such as how you curb appeal into an algorithm or consider luxury homes in neighborhoods with median incomes.
Relying solely on online estimates to value your home can result in overvaluing or undervaluing. Use them only as guides; always seek professional appraisal or CMA services before finalizing a price for any transaction.
How Accurate Are Redfin, Zillow, And Realtor.Com Estimates?
Unfortunately, not as you might imagine. All three services take pride in using up-to-date data in their estimates.
Still, all have significant margins of error that make their estimates inaccurate. Redfin's median error for off-market property estimates stands at 8.7%. In comparison, its on-market estimates fall within an error range of 3-4% meaning an estimate may differ by up to $26,000 in either direction.
Zillow offers slightly lower margins of error 6.9% for properties not currently listed and 1.9% for those that are listed than comparable sites.
However, its results should never replace professional appraisal. Errors arise because these platforms use different data sources; Redfin Estimates and Zillow Zestimates both employ proprietary algorithms derived from publicly accessible information sources.
- Market trends.
- Recent Sales.
- Tax records.
- Comparable homes.
- Rates of insurance and lending.
Comparable Homes Rates of Insurance and Lending Realtor.com recently unveiled three estimators: Quantarium, CoreLogic, and Collateral Analytics; it would be wise to utilize each estimator on every property before consulting an appraiser for additional safety.
Redfin Vs. Zillow And Realtor.Com: Pros & Cons
Redfin Pros
- Home sellers can get substantial discounts, and buyers can receive rebates.
- The best for teams of agents.
- Agents who are salaried plus agents earning commissions.
- The best support for remote sales is 3D virtual tours, professional photography, and other services.
Redfin Cons
- Agents are more likely to become overworked if they have 3x the number of customers.
- Home buyers and sellers receive less hands-on support.
- Redfin's savings on agent fees is only worthwhile if you can buy and sell within 12 months. This is not easy to do.
- Redfin will only display FSBO listings posted on other websites (e.g., FSBO.com).
Zillow Pros
- The largest database of property listings, with an estimated 135 million listings.
- FSBO listings: Sellers can add their properties manually to Zillow.
- Sorting properties by detail is the best way to find your ideal home.
- Zillow Premier Agent Program for Lead Generation and Advertising.
- Apps for homeowners, agents, and buyers.
Zillow Cons
- Zillow Zestimates provide a large margin of error when determining whether a property is for sale.
- Fees for the new or upcoming agents in the agent program.
Realtor.com Pros
- Realtor.com aggregates 99% of the MLS listings.
- MLS database refreshes every 15 minutes to ensure accuracy in high-paced markets.
- Pre-qualification tools and loan calculators are among the better financing resources.
- Find properties in your school district.
- Find a Realtor search is highly accurate.
Realtor.com Cons
- No FSBO listings support.
- Exclusive realtor spots in your ZIP code are paid for by agents at a premium.
- Zillow typically has 3x the traffic of Realtor.com.
Which Real Estate Listing Platform Offers The Best Leads?
With these platforms competing for market share, the Redfin vs. Zillow battle will continue unabated. In contrast, Realtor.com continues its stronghold among real estate agents, sellers, and buyers.
Which platform works best depends on budget, location, and experience, so it pays to try all three platforms and discover which works for your business and yourself.
Email leads are integral to redfin app, Zillow and Realtor.com lead generation strategies.
Your real estate leads will soon arrive in your inbox, where CISIN's lead extraction software will extract all pertinent lead data for analysis. Get in touch today to discover how CISIN can support your lead generation strategy.
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The Conclusion Of The Article Is:
It's reasonable to wonder, like with any AI-enhanced software program that improves over time and becomes more efficient, whether real estate professionals who take part in Zillow Offers are helping create something that may one day replace their jobs altogether.
Although experts would never claim machines will fully replace humans in Zillow offers entirely, they conceded it wouldn't make much sense not having all options available could work better and said both elements "will always make for a better experience." They concluded by writing,
