Netflix’s new “The Social Dilemma” documentary has been eye-opening for millions of viewers (see in: hundustantimes, dotcom), sparking conversation — and concern — about how the algorithms used by social media platforms manipulate human behavior.
Here is: “AI is Neutral Technology: What May be Harmful in Social Media Can Help Healthcare — By Dr. Darren Schulte, MD is Chief Executive Officer at Apixio.
By leveraging artificial intelligence that has become shockingly good at analyzing, predicting, and influencing user behavior. The film asserts that the resulting unintended consequences have created real-life dystopian implications: excessive screen time that causes real-world relationships to suffer, addictive behavior, alarming societal divisiveness, and even higher rates of depression, self-harm, and suicide.
These consequences as users look to social media for validation. Big tech corporations profit enormously by harvesting and analyzing their user data and manipulating their behavior to benefit advertisers.
While the film appears to give machine learning algorithms a bad rap, these algorithms aren’t inherently evil. It all depends upon what the algorithms are trained to do.
In fact, the use of AI algorithms in healthcare has tremendous potential to transform health care by improving individual patient outcomes and overall population health, enabling more personalized medicine, reducing waste and costs, and accelerating the discovery of new treatment and preventative measures.
The same type of algorithms showcased in the Social Dilemma can be trained to analyze data generated by patients, care providers, and devices (like wearables).
The algorithms can even use surveillance of body functions (like lab tests and vital signs) to provide deeper and more accurate insight into individual health, health-related habits, and behaviors over time.
By combining that individual data with anonymous, aggregated population data, we can discover better treatments, refine clinical guidelines, and discover new therapies to improve overall population health.
- Improve response to emergent diseases like COVID-19. One of the problems we’ve had with effectively treating COVID-19 patients is that there’s been a lot of experimentation and trial-and-error. However, even the data on the results of those therapies has been slow to propagate across the global medical community.
Hospitals and physicians only have data on the patients that they are treating themselves. With no cohesive system for sharing patient data. Providers in America, for example, have not been able to benefit quickly enough from the knowledge and experience of providers in Asia and Europe — where the virus spread first.
By leveraging AI to mine aggregated medical records from millions of individuals, we could see what treatments have been most effective for specific patient cohorts.
Even further, we could analyze the characteristics of those already infected to see which attributes make one more likely to develop the most severe symptoms. By identifying vulnerable populations faster, we can then take targeted steps to prevent infection and implement the most effective treatments.
As we have seen, the analysis and exchange of this data manually, takes far too long, contributing to the propagation and death toll. With AI, we can surface this knowledge much faster and potentially reduce the impact of the next novel disease.
- Provide better patient surveillance. Identifying how – and how fast – COVID-19 spreads has also been a significant challenge. Scientists traditionally use a metric called R0 (pronounced “R naught”), a measure of the average number of people infected by one infectious individual.
Using R0 to predict COVID-19’s spread has been problematic for several reasons, including the fact that different groups use different models and data, and asymptomatic individuals can spread the disease without knowing that they are infected.
AI can help resolve this issue to improve patient surveillance by analyzing both medical records of patients who tested positive alongside contact tracing data that indicates the potential for infection. By combining this data and analyzing it at scale, medical authorities can use this insight to determine where to implement aggressive testing programs and more restrictive shelter-in-place measures to slow the spread of disease.
- Improve the quality of care. Health care providers want to deliver the best quality of care to their patients. But one of the challenges they face is measuring quality and patient outcomes with empirical evidence. With patient data scattered across different sources like electronic health records (EHRs), lab results, imaging studies, it is difficult to aggregate and analyze.
By implementing systems that consolidate this data and allow providers to use AI to mine it for insights, physician practices and hospitals can identify trends among patients and implement quality improvement programs.
For example, if they see that individuals with certain characteristics fail to follow-up on important health concerns, providers can intervene with appointment reminders, transportation resources, provide telehealth options, or other interventions to keep patients engaged in their own care.
On the flip side, insurers are also concerned about care quality and ensuring patients get the best possible outcome at the lowest possible cost.
AI can help insurers track and measure patient outcomes as they move through the care system—from a primary care provider to a specialist to a hospital for surgery and into a rehab facility, for example—and identify providers or treatment protocols that may not be delivering optimal results. Insurers can then work with providers to implement new approaches to improve success rates and overall patient outcomes.
- Identify and mitigate concerning trends. During a typical patient encounter, doctors only have access to the medical information for the patient in front of them. Consulting their patient history provides a limited view of factors that might indicate declining health. With data scattered across different systems, doctors do not always have all the data they need at hand.
AI can help surface broader indicators that a patient’s health may be declining over time.
By analyzing aggregate data across a large population, AI can show that patients with certain vital signs or trends in their data might be headed toward developing certain conditions, like diabetes or heart disease.
Physicians can use this information as a predictor of potential trouble and begin implementing preventative action. Some solutions can alert physicians to these insights as notifications within the Electronic Health Record (EHR) during the patient encounter. This allows physicians to take swift action to prevent disease progression.
- Enable personalized medicine. The health care industry has been moving toward personalized medicine for years, aiming to transform the “one-size-fits-all” approach to care into a customized plan for each individual. But this is practically impossible without access to aggregated data and insights that only AI can provide.
Consider the AI social media companies use to create and leverage personas to prompt engagement and drive advertising dollars. If we were to apply the same technique to build health care personas for each person, we could then provide this information to providers (with the patient’s permission).
Providers could then use tools like notifications, nudges, cues, or other communication (just like social media) to elicit positive behavior for better health.
For example, providers could target at-risk patients with prescription reminders, diet recommendations, or other resources relevant to their specific health situation.
- Reduce diagnostic and treatment errors. Even the best providers can overlook important details and make mistakes, especially with the pressure they are under to squeeze more patients into a typical day.
Just as algorithms can help social platforms surface insights about their audience to woo advertisers, physicians can use algorithms to surface insights to diagnose and treat conditions accurately. For example, AI can highlight confounding conditions or risk factors for patients, allowing doctors to consider the individual’s entire health profile when making decisions.
AI can also aid in surfacing potential drug interactions that could put patients at risk. All of this can substantially lower the risk of errors that cause patients harm, not to mention reduce the risk of malpractice accusations.
The same way algorithms can identify Facebook users who might be interested in a new lawnmower and serve up an appropriate ad; they can help providers identify high-risk patients before they develop costly care needs. By culling through data to identify risk factors, AI allows providers to implement preventative and early intervention strategies.
For example, an algorithm might spot a specific obesity indicator that correlates with the risk for Type II diabetes or identify patients with high blood pressure that are at greater risk of heart attack, stroke, or kidney disease.
These insights can be delivered at the point of care, even during a patient encounter. If a patient displays a specific set of symptoms, as the data is entered into the EHR, the physician is alerted to the risk and can review trends in disease progression or confounding conditions to plot the best course of action.
- Identify optimal treatment pathways through data-based referrals. Traditionally, when a patient needed to see a specialist, for surgery or physical therapy, for example, physicians typically referred to providers with whom they have existing relationships.
Unfortunately for patients, this does not always mean they get the best care for their unique situation. Does the provider have experience working with patients with co-morbidities? Do they specialize in complex surgeries or more typical procedures?
AI allows providers to refer to the best provider for each patient’s unique needs based on hard evidence of success and proven outcomes, rather than simply based on existing ties.
For example, if a patient with diabetes needs a knee replacement, AI can help primary care providers to identify orthopedic specialists and rehabilitation providers with proven, demonstrably better results in handling patients with this co-existing condition.
- Reduce spending waste. About 30% of healthcare spending is considered “waste,” totaling up to $935 billion. Nearly $80 billion alone can be attributed to overtreatment or low-value care.
In other words, providers order more tests, services, and procedures that aren’t necessarily the best option—or even necessary at all—mostly in an effort to protect themselves against being accused of not doing enough and to meet insurer’s requirements (e.g., ordering x-rays before an MRI when an injury is clearly soft tissue related or sending patients for multiple repeat mammograms before conducting an ultrasound to evaluate a suspicious lump).
By mining data using algorithms, providers and insurers can focus on using the tests and procedures that demonstrate high value or necessary for specific instances. For example, is it necessary for patients on certain medications to get blood tests every 90 days? Do wellness visits add value to patients?
By looking at what is most effective across the larger population, AI can help point physicians in the right direction earlier, reducing unnecessary diagnostics and placing the patient on the path to better health more quickly.
AI thereby can reduce wasteful spending by identifying diagnostics that are most effective and economical, potentially saving patients and payers millions every year on ineffective tests and treatments.
- Accelerate drug and treatment discovery. The current pathway to new drugs, vaccines, and treatments is long and arduous. On average, it takes at least ten years for new drugs to go from discovery to marketplace, with trials alone taking as long as seven years on average. For new vaccines, the average time to market is up to 12 years (which puts hope for a COVID-19 vaccine by year’s end into perspective).
One of the reasons the process is so slow is the lack of advanced data and analytics capabilities in the process.
The use of AI to analyze patient and drug performance data could substantially accelerate the time to market for new drugs and vaccines, which could save lives.
Just as the lack of data analytics meant doctors struggled to devise effective COVID-19 protocols, the inability to rapidly analyze trial data and evaluate new use cases for existing drugs prevents patients from getting the treatment they need.
Algorithms can accelerate this analysis and get much-needed medicines into the hands of patients faster.
All this time can add up to a significant cost and take away from time spent in direct, face-to-face time with patients.
AI can help reduce this burden and lower operational costs by automating manual processes like prior authorizations, reducing retrospective chart reviews by surfacing the right data to the right people earlier. The right data, quickly obtainable, will help physicians make better, faster decisions.
These efficiencies enabled by AI, on the administrative side, ultimately lower the cost of health care services for both patients and payers and frees up more resources to improve direct patient care.
The negative use of social media comes when the data influences human behavior bringing negative consequences.
For the most part, technology is neutral. But in the wrong hands with the wrong motives or objectives, the use of algorithms can raise serious ethical questions.
The same algorithms that cause us to feel more anxious, isolated, or depressed when leveraged by social media can also be used to help us heal, stay healthy, and achieve optimal well-being.
The questions are all about the algorithm’s objective and training, testing, and user feedback data that are used by the algorithm. The reality is that managing both individual and public health in the 21st century requires access to data and insights.
Without data-driven insights, we are just guessing what will work in healthcare and what doesn’t.
Leveraging algorithms to analyze health care data empowers physicians to devise a truly personalized care plan for each individual. The physician can improve the quality of care overall and lower health care costs by tapping into collective insight and knowledge gleaned from millions of patient records.
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How Blockchain Is Being Used With Smart Buildings – ReadWrite
Whether you realize it or not, many of us live in buildings with some smart capacity. You probably have at least one smart device in your home.
With the smart device industry set to grow by $65 billion by 2024, the odds are, you’ll add more of these devices. The true potential of smart homes lies in the ability of smart devices to communicate together — and that’s where blockchain technology comes in.
How Blockchain is Being Used With Smart Buildings
On the surface, smart technologies make individual tasks easier, but the potential is much larger than that. A smart device is effectively a sensor able to collect significant amounts of data about everything, from your energy use to how well-stocked your fridge is.
Smart Technology Works Better in Swarms
On its own, this data is valuable; when combined with data from other devices, its usability becomes game-changing. A properly connected smart home would be able to automatically adjust the heating to your preferences while minimizing bills, ordering your favorite groceries, monitoring and adjusting energy usage, sending repair notifications if something breaks, and much more.
Internet of Things (IoT) technologies are already used extensively in supply chain management. They help efficiently manage products passed through multiple stakeholders and verify that products are what the label says they are.
Catching Slave Labor in Fishing Supply Chains
One example where smart technology has been useful is in tracking fishing supply chains. The World Wildlife Federation (WWF) has used IoT to track sustainable tuna fishing.
The Western and Central Pacific tuna trade is rife with illegal fisheries — and, in some cases, slave labor — because tracking is either done via an easily-forged paper trail or not at all. However, savvy consumers and brands are demanding more accountability from the tuna industry.
The WWF’s branches in New Zealand, Australia, and Fiji have combined forces with blockchain software studio ConsenSys to implement secure traceability and track to address the problem.
Radio-frequency identification (RFID) or QR codes capture information as a fish moves through the supply chain from the boat to grocers. Tracking information is automatically saved in blockchain, making it nearly impossible to forge.
Privacy and Compatibility Remain a Concern
Although smart technology has many uses in enterprise settings, it becomes a thornier prospect for individuals. IoT devices collect huge amounts of data which can reveal a lot about their owners. Additionally, they are often poorly secured, creating significant security challenges.
Most smart devices must run on centralized platforms controlled by major tech companies, notably Amazon and Google.
There have been significant privacy concerns about both companies due to their access to an extraordinary amount of personal data.
Amazon Alexa’s Vulnerabilities
Setting aside concerns about microphones, Amazon’s voice-activated assistant Alexa also presents other significant security concerns.
Although Amazon provides some privacy protections, with 100 – 200 million Alexa devices and over 100,000 skills already deployed, there is a significant concern about malicious developers taking advantage of security holes.
For example, developer names aren’t verified, allowing a malicious developer to stage a phishing attack posing as a different company. This risk is especially high with some skills that link to email, banking, or social media accounts.
After a skill has been approved and added to the marketplace, a malicious developer can change its coding without getting Amazon’s approval or notifying the customer. Many developers also have misleading privacy policies — or none at all, meaning that customers will have no idea how their personally identifiable information will be used.
Lack of Device Compatibility
The second challenge is compatibility. Early adopters are painfully familiar with the concept of device divorce, where two smart devices cannot speak with another. Part of the problem is that Amazon and Google are used as primary smart home controllers, and there isn’t a platform-agnostic solution widely available to most consumers.
Blockchain Technology is the Missing Piece of the Puzzle
Blockchain technologies are working to provide the solution to these challenges and others since they can enable P2P connections without the need for a centralized validator.
With blockchain, it would be possible to connect numerous smart devices without being forced to hand that data directly over to the device manufacturer, mitigating privacy and security concerns. It can also provide increased transparency over how data is used, helping users understand what data their smart home is collecting and what it’s used for.
Blockchain technology is also hardware agnostic. Thus, it would be possible for users to pair together devices from different manufacturers without worrying about compatibility.
IOTA’s Tangle vs. Traditional Blockchain
One of the best examples of this vision is the IoT-focused blockchain IOTA.
It is important to understand that we are not talking about financial blockchain technology like Bitcoin. Blockchains based on traditional Proof of Work (PoW), like Bitcoin, lack the speed and scalability necessary to process the millions of data points produced by smart devices.
Instead, we are looking at smart device-focused technologies, most notably IOTA. IOTA uses a Tangle specifically designed for data and value transfer.
Blockchains like Bitcoin are essentially long chains of blocks containing transactions. The Tangle, on the other hand, is constructed as a directed acyclic graph (DAG), which is a collection of vertices connected by edges.
IOTA’s implementation is designed in such a way that each new transaction (vertice) must approve two previous transactions when it enters the Tangle. This eliminates the need for Proof of Stake (PoS) or PoW consensus methods.
Because these transactions don’t require always-online validators, they are feeless and contain metadata that makes them suitable for micropayments and data transfer.
IOTA is interesting because the technology is more mature than many other IoT-focused blockchain solutions. The project has experienced past problems, but the roll-out of its improved Tangle has allowed it to secure some important partnerships, primarily in areas designed to improve transparency.
Properly Validating Smart Device Data Is The First Step
IOTA’s most important partnership for smart homes is undoubtedly Project Alvarium. The biggest challenge posed by IoT — and smart devices in general — is the sheer volume of data collected. The vastness of information makes assessing what data is trustworthy and useful difficult, especially in an automated environment.
To solve this problem, Dell and IOTA teamed up to create Project Alvarium, designed to provide a simple way to assess the trustworthiness of data gathered.
Project Alvarium’s system logs every datapoint as it travels across the system. Each interaction is given a trust rating, which is logged on the IOTA Tangle to prevent tampering. This provides a simple way to find problems or deliberate tampering within a network of data.
Blockchain Can Help Resolve Security Concerns About Smart Security
When smart home users are certain that they can trust the data being generated by their devices, it opens up a world of opportunities that could transform our daily lives.
The most immediate use of blockchain technology is in improving building security. The most high-profile problem is undoubtedly Amazon’s Ring. In late 2020, dozens of people sued Amazon over accusations that their Ring doorbells had been breached.
The breach enabled hackers to watch people inside their homes and talk to individuals in the house over the Ring speakers.
The Blockchain Difference
Blockchain has been shown to resolve both the problem of data breaches as well as hacking takeovers. Capturing a blockchain-powered device would require compromising the entire blockchain itself compromised.
But proper validation, such as that proposed by IOTA, allows malicious devices to be pruned from the network, significantly improving security.
Additionally, blockchain could enable consumers to understand how their data is being used, helping to make smart devices more privacy-focused.
Smart Building Management Solutions are Already Being Tested
The value of blockchain technology becomes even bigger at scale. One of the most impactful uses of IoT and blockchain technology is in building management. Whether for an apartment building or an office building, it’s often difficult to effectively manage a building’s heating, lighting, and security in a way that minimizes waste.
Example: How Blockchain Could Manage Heating Bills
In a traditional setting, most buildings are managed centrally. If there is a unified heating system, it is often controlled by the local administration. Although this system is more efficient than individually-heated buildings, there is significant room for human error. That’s because the system is not optimized to account for more efficient heating higher up in the building as heat rises.
A network of heating sensors could be used to automatically measure the temperature in each apartment or office in a building. If the different thermostats could communicate with each other, it should be possible to input all the data into a blockchain solution.
A scheme like this would allow the building operators to create a proper heat map of the building and understand the most efficient usage of energy. It would also enable residents to access the data and understand why the system works the way it does.
Theoretically, it could also enable a user to select a target temperature for their apartment by leveraging rising heat from lower apartments.
Solutions on the Horizon
This kind of project is already being tested. For example, Brickschain offers several products that minimize difficulties with building management and handover on sale. There are also an increasing number of studies looking at how blockchain can be positively implemented into the building management process.
The Future of IoT: Many-to-Many Marketplaces
When buildings are utilizing IoT devices and blockchains, a bigger opportunity opens up: decentralized marketplaces.
Currently, it can be difficult to get the best deal on energy or heating bills because it is a marketplace with many customers but only a few providers. Switching providers can be difficult and doesn’t guarantee a competitive rate.
However, with blockchain, it would be possible to change providers based on real-time pricing data. This setup would create a competitive many-to-many environment where many providers are looking to sell energy to many customers. The competition among providers would drive down energy prices and improve overall efficiency in energy markets.
Swedish District Heating Study
Sweden has conducted studies to investigate the utility of blockchain for a district heating market. The setup allows apartment blocks already utilizing blockchain to automatically select the most affordable provider at any given moment, minimizing bills without requiring micromanagement.
The same concept could be applied to many aspects of building management.
One interesting idea is the concept of decentralized governance. This type of network could empower tenants and apartment owners to vote on changes to their apartment block’s management proceedings.
For example, renters could vote in favor of using only green energy sources or for changes to living space regulations. Building administrators could then better understand their occupants’ needs and create a better living environment for all involved.
Blockchain Will be Needed to do IoT Correctly
Adoption of IoT and smart technologies will likely increase. Governments like the UK are already pushing hard on smart meters and many of us have already adopted some form of smart technology in our homes.
This rush to adopt new technology will undoubtedly come with significant scaling problems as well as security concerns and significant privacy issues.
Additionally, a market dominated by a handful of major tech companies like Amazon and Google could prove damaging to the consumer in the long term.
To counter these eventualities, we’ll need a platform-agnostic solution that allows a more diverse field of producers to create new IoT devices.
Blockchain technology still represents the best way to utilize IoT for everyone’s benefit. If solutions like IOTA are implemented into existing smart homes, then we could build a new decentralized marketplace that will give us better control of our data, while improving the efficiency of our homes.
Image Credit: pixabay; thank you!
Social Sign-on: Sure, it’s convenient. But is it really safe? – ReadWrite
Remembering passwords is always a hassle, especially when you have innumerable websites that require logging in to view or interact with their content. To make the process simpler (as little as a couple of clicks), webmasters worldwide have accepted and implemented social logins on their websites.
Social Sign-on: Sure, it’s convenient. But is it really safe?
So, what exactly is social login? How different is it compared to the traditional method of inputting your credentials such as username, email address and password manually? More importantly, is it safe enough for use on all kinds of browsing activities?
In this article, we answer all the above questions and more, helping you understand what social sign-on is, and what the disadvantages of this convenient method are.
The history of social logins
Social sign-on as a method of hassle-free authentication has been around for over a decade now. Back in the nascent days of the modern internet in 2008, Facebook launched Facebook Connect, a service aimed at simplifying registrations on websites.
Once webmasters enabled FB Connect on their websites, visitors to the site would no longer need to fill up lengthy registration forms to sign up for the website’s offerings.
All they needed to do was connect their existing Facebook account to the website, enabling direct access to the site with a click of a button.
In 2009 and 2010, Twitter and LinkedIn respectively enabled their users to socially login to other sites using their existing social network credentials.
Google+ followed suit in 2011, and although no longer active as Google+, it still supports social sign-on using a Google account.
While it all sounds very convenient, social sign-on has many drawbacks and challenges that impact both website visitors and website owners.
Social Sign-on: The challenges and disadvantages
The Trust Factor
Most internet users do not trust the websites they browse to store and utilize their personal information safely and responsibly. Often, website visitors are concerned about how the information they have shared will be used.
In a June 2020 survey conducted by Insider Intelligence, 32% of US Facebook users felt that they somewhat disagreed that the platform could keep their data and privacy secure.
People tend to be wary of the private information they share online; they often resort to uploading falsified or inaccurate information about themselves on social media.
Considering that these social media sites do not verify or vouch for the authenticity of their user’s information, this could be less than ideal for a website looking for accurate data while accepting new user registrations.
In 2019, Facebook released data that said that 16% of the accounts on its platform are fake/duplicate accounts created by individuals or companies. What’s more worrisome are the findings of the research team at NATO StratCom that suggest 95% of the reported fake accounts still continued to remain active, with no action taken by the social media website.
With no checks on the actual profile that’s being used to socially sign-on to your website, you could soon have an imposter, Donald Trump or Joe Biden signing up for your global warming newsletter or purchasing a bag of your freshly powdered Mexican coffee.
Not everyone’s social — nor on social
While we talk about social media, we need to understand that although it is a global phenomenon with an insanely large number (read 3.6 billion) of people using it, there is still a sizeable chunk (>50%) of the population that is not on social media.
Using a restrictive method, you risk alienating a section of society that could be your potential target audience.
Transfer of Power
Enabling social sign-on seems pretty enticing at first, considering it would cut down your authentication work significantly. But this very ‘benefit’ could end up costing you dearly, as you lose control over your visitors’ data to a third-party service provider, i.e., the social media network.
Should there be any downtime at the social media service’s end, your website visitors would be stranded, unable to login to your site or access their data?
Access Control Issues
Many internet access places tend to have controls in place when it comes to accessing social media. For example, corporate and educational networks generally block access to social websites. Certain countries like Iran, China, Syria, and North Korea have blanket bans on the most popular social websites.
Social sign-on still depends on an API call-back to the social networking site to authenticate the user. Thus, by having social sign-on set up on your website, visitors authenticating on your site through these networks would end up facing a website with broken functionality.
Social media accounts are often the target of several hacking and phishing attempts. Thus, if your user’s social media account is hacked, it could lead to their account on your site being compromised as a result.
A University of Maryland study revealed a hacking attempt every 39 seconds on average, affecting a third of Americans every year.
Hacked social accounts could have an adverse impact on your website as well, by performing activities that might eat up your server resources or corrupt your files, if your security is not up to the mark. Secure authentication is the need of the hour, and knowledge of the security practices will help solve these concerns.
Too much to choose
People use many social media websites, so keeping a single social login can be counterproductive. However, providing multiple methods to login could likely confuse or overwhelm your visitor, leading to lower conversion or sign-up rates.
Lesser data to work with
Using a social sign-on for your website would mean limited access to user data, especially email. Not every social media network allows websites to access the customer’s email address. For businesses that rely on customer information for lead generation, this would be a major deal-breaker.
Awareness of all the security practices and malpractices (sawolabs dotcom) will help educate users as well as the website owners.
If not social sign-on, then what?
All the above drawbacks would make webmasters question the efficacy of social sign-on. But then, is there a better alternative that does not include such shortcomings?
Say hello to passwordless authentication powered by SAWO Labs. A new-age solution designed to address all concerns of security, compatibility and functionality.
Image Credit: yellow graphic — from author; thank you!
Top Image Credit: karolina grabowska; pexels; thank you!
3 Ways Companies Can Be More Sustainable – ReadWrite
I’m thinking about our planet today — I think about our planet every day. Our planet is hurting, and many businesses are encouraging their employees to live more sustainably. According to the Environmental Protection Agency (EPA), industry and agriculture account for approximately 32 percent of direct emissions.
3 Ways Companies Can Be More Sustainable
Here are a few ways companies can encourage sustainability in their employees and work to lower the remaining 68 percent.
Employ a hybrid work model
With so many people working from home due to the COVID-19 pandemic, we’ve inadvertently been doing Earth a huge favor. The EPA shows that transportation is responsible for 28 percent of greenhouse gas emissions, with about half of that coming from personal vehicles that burn gasoline and diesel. Because many companies instituted a work from home policy, there were fewer cars on the road and fewer greenhouse gas emissions. Companies can continue this progress by instituting a hybrid work model once the pandemic is finally over.
Reduce waste in the office
One big way to reduce waste in the office is by offering snack and drink options that eliminate single-use plastic. For example, TechnologyAdvice uses a Bevi machine in the office, offering still, sparkling, and flavored water without single-use plastic. You might also consider snacks that don’t need to be individually packaged, like fruits or nuts.
While you may not be able to completely eliminate office waste, you can work to offset the waste you do generate. Make it easy for employees to recycle and encourage them to do so. You can create an employee-led recycling program, keep an “I don’t know” bin for those items that don’t always fall into the normal categories, and create challenges around recycling goals.
Continual education about climate change
However you decide to encourage sustainability in your office, it’s important that both you and your employees engage in continual education about climate change. Thanks to the different forms of media available today, educating yourself about climate change has never been easier.
For podcast listeners, consider checking out How To Save A Planet. It’s a Spotify original podcast hosted by scientist Dr. Ayana Elizabeth Johnson and journalist Alex Blumberg, and it is the exact opposite of what people think when they hear “climate change resource:” it’s inspiring instead of depressing, entertaining, so accessible, and has great intro music.
Another Earth-friendly podcast you should listen to is Stories for Earth, which examines how climate change is discussed in pop culture.
If you like documentaries, check out Before the Flood, which was made by Leonardo Di Caprio and National Geographic. If you are a reader, consider these three: No One Is Too Small To Make A Difference by Greta Thunberg, All We Can Save edited by Ayana Elizabeth Johnson and Katherine Hayhoe, and The Future Earth by Eric Holthaus.
Image Credit: karolina grabowska; pexels; thank you!