What Is the 83(b) Election?

The 83(b) election is a provision under the Internal Revenue Code (IRC) that gives an employee, or startup founder, the option to pay taxes on the total fair market value of restricted stock at the time of granting.

Understanding the 83(b) Election

The 83(b) election applies to equity that is subject to vesting, and it alerts the Internal Revenue Service (IRS) to tax the elector for the ownership at the time of granting, rather than at the time of stock vesting.

The 83(b) election documents must be sent to the IRS within 30 days after the issuing of restricted shares. In addition to notifying the IRS of the election, the recipient of the equity must also submit a copy of the completed election form to their employer.

In effect, an 83(b) election means that you pre-pay your tax liability on a low valuation, assuming the equity value increases in the following years. However, if the value of the company instead declines consistently and continuously, this tax strategy would ultimately mean that you overpaid in taxes by pre-paying on higher equity valuation.

Typically, when a founder or employee receives compensation of equity in a company, the stake is subject to income tax according to its value. The fair market value of the equity at the time of the granting or transfer is the basis for the assessment of tax liability. The tax due must be paid in the actual year the stock is issued or transferred.

However, in many cases, the individual receives equity vesting over several years. Employees may earn company shares as they remain employed over time. In which case, the tax on the equity value is due at the time of vesting. If the company’s value grows over the vesting period, the tax paid during each vested year will also rise in accordance.

Example of an 83(b) Election

For example, a co-founder of a company is granted 1 million shares subject to vesting and valued at $0.001 at the time the shares are granted. At this time, the shares are worth the par value of $0.001 x number of shares, or $1,000, which the co-founder pays. The shares represent a 10% ownership of the firm for the co-founder and will be vested over a period of five years, which means that they will receive 200,000 shares every year for five years. In each of the five vested years, they will have to pay tax on the fair market value of the 200,000 shares vested. 

If the total value of the company’s equity increases to $100,000, then the co-founder’s 10% value increases to $10,000 from $1,000. The co-founder’s tax liability for year 1 will be deduced from ($10,000 – $1,000) x 20% i.e. in effect, ($100,000 – $10,000) x 10% x 20% = $1,800.

• $100,000 is the Year 1 value of the firm
• $10,000 is the value of the firm at inception or the book value
• 10% is the ownership stake of the co-founder
• 20% represents the 5-year vesting period for the co-founder’s 1 million shares (200,000 shares/1 million shares)

If, in year 2, the stock value increases further to $500,000, then the co-founder’s taxes will be ($500,000 – $10,000) x 10% x 20% = $9,800. By year 3, the value goes up to $1 million and the tax liability will be assessed from ($1 million – $10,000) x 10% x 20% = $19,800. Of course, if the total value of equity keeps climbing in Year 4 and Year 5, the co-founder’s additional taxable income will also increase for each of the years.

If at a later time, all the shares sell for a profit, the co-founder will be subject to a capital gains tax on his gain from the proceeds of the sale.

83(b) Election Tax Strategy

The 83(b) election gives the co-founder the option to pay taxes on the equity upfront before the vesting period starts. This tax strategy will only require that tax be paid on the book value of $1,000. The 83(b) election notifies the IRS that the elector has opted to report the difference between the amount paid for the stock and the fair market value of the stock as taxable income. The share value during the 5-year vesting period will not matter as the co-founder won’t pay any additional tax and gets to retain the vested shares. However, if the shares for sold for a profit, a capital gains tax will be applied. 

Following our example above, if the co-founder makes an 83(b) election to pay tax on the value of the stock upon issuance, the tax assessment will be made on $1,000 only. If the stock is sold after, say, ten years for $250,000, the taxable capital gain will be on $249,000 ($250,000 – $1,000 = $249,000).

The 83(b) election makes the most sense when the elector is sure that the value of the shares is going to increase over the coming years. Also, if the amount of income reported is small at the time of granting, an 83(b) election might be beneficial.

In a reverse scenario where the 83(b) election was triggered, and the equity value falls or the company files for bankruptcy, then the taxpayer overpaid in taxes for shares with a lesser or worthless amount. Unfortunately, the IRS does not allow an overpayment claim of taxes under the 83(b) election. For example, consider an employee whose total tax liability upfront after filing for an 83(b) election is $50,000. Since the vested stock proceeds to decline over a 4-year vesting period, they would have been better off without the 83(b) election, paying an annual tax on the reduced value of the vested equity for each of the four years, assuming the decline is significant.

Another instance where an 83(b) election would turn out to be a disadvantage will be if the employee leaves the firm before the vesting period is over. In this case, they would have paid taxes on shares that would never be received. Also, if the amount of reported income is substantial at the time of stock granting, filing for an 83(b) election will not make much sense.

What Is a 51% Attack?

A 51% attack is an attack on a cryptocurrency blockchain by a group of miners who control more than 50% of the network’s mining hash rate. Owning 51% of the nodes on the network gives the controlling parties the power to alter the blockchain.

The attackers would be able to prevent new transactions from gaining confirmations, allowing them to halt payments between some or all users. They would also be able to reverse transactions that were completed while they were in control. Reversing transactions could allow them to double-spend coins, one of the issues consensus mechanisms like proof-of-work were created to prevent.

Understanding a 51% Attack

A blockchain is a distributed ledger—essentially a database—that records transactions and information about them and then encrypts the data. The blockchain’s network reaches a majority consensus about transactions through a validation process, and the blocks where the information is stored are sealed. The blocks are linked together via cryptographic techniques where previous block information is recorded in each block. This makes the blocks nearly impossible to alter once they are confirmed enough times.

The 51% attack is an attack on the blockchain, where a group controls more than 50% of the hashing power—the computing that solves the cryptographic puzzle— of the network. This group then introduces an altered blockchain to the network at a very specific point in the blockchain, which is theoretically accepted by the network because the attackers would own most of it.

Changing historical blocks—transactions locked in before the start of the attack—would be extremely difficult even in the event of a 51% attack. The further back the transactions are, the more difficult it is to change them. It would be impossible to change transactions before a checkpoint, where transactions become permanent in Bitcoin’s blockchain.

Attacks Are Prohibitively Expensive

A 51% attack is a very difficult and challenging task on a cryptocurrency with a large participation rate. In most cases, the group of attackers would need to be able to control the necessary 51% and have created an alternate blockchain that can be inserted at the right time. Then, they would need to out-hash the main network. The cost of doing this is one of the most significant factors that prevent a 51% attack.

For example, the most advanced application-specific integrated circuit (ASIC) miner is the Bitmain S19 XP Hydro. It costs more than $19,800 and has a hash rate of 255 terahashes per second (TH/s).

The top three mining pools by hashrate are:

• FoundryUSA, at 54.42 exahashes per second (EH/s); 23.75% of the total Bitcoin network hashrate
• AntPool, at 41.49 EH/s; 18.12% of the total Bitcoin network hashrate
• Binance Pool, at 34.48 EH/s; 15.06% of the total network hashrate

Combined, these three pools make up 56.93% of the network hashrate, a whopping 130.4 EH/s (1.304 million TH/s). To equal that hashrate, the attackers would need more than 511,373 S19 XP Hydros—which would put fixed costs close to $10.13 billion, plus a building to host the equipment, maintenance staff, electricity, and cooling.

Major cryptocurrencies, such as Bitcoin, are unlikely to suffer from 51% attacks due to the prohibitive cost of acquiring that much hashing power. For that reason, 51% attacks are generally limited to cryptocurrencies with less participation and hashing power.

After Ethereum’s transition to proof-of-stake, a 51% attack on the Ethereum blockchain became even more expensive. To conduct this attack, a user or group would need to own 51% of the staked ETH on the network. It is possible for someone to own that much ETH, but it’s unlikely; according to Beaconchain, more than 13.8 million ETH were staked at the end of September 2022. An entity would need to own more than 6.9 million ETH (more than $9 billion worth) to attempt an attack.

Once the attack started, the consensus mechanism would likely recognize it and immediately slash the staked ETH, costing the attacker an extraordinary amount of money. Additionally, the community can vote to restore the “honest” chain, so an attacker would lose all of their ETH just to see the damage repaired.

Attack Timing

In addition to the costs, a group that attempts to attack the network using a 51% attack must not only control 51% of the network but must also introduce the altered blockchain at a very precise time. Even if they own 51% of the network hashing rate, they still might not be able to keep up with the block creation rate or get their chain inserted before valid new blocks are created by the ‘honest’ blockchain network.

Again, this is possible on smaller cryptocurrency networks because there is less participation and lower hash rates. Large networks make it nearly impossible to introduce an altered blockchain.

Outcome of a Successful Attack

In the event of a successful attack, the attackers could block other users’ transactions or reverse them and spend the same cryptocurrency again. This vulnerability, known as double-spending, is the digital equivalent of a perfect counterfeit. It is also the basic cryptographic hurdle blockchain consensus mechanisms were designed to overcome.

Successful 51% attackers may also implement a Denial-of-Service (DoS) attack, where they block the addresses of other miners for the period they control the network. This keeps the “honest” miners from reacquiring control of the network before the dishonest chain becomes permanent.

Who Is at Risk of 51% Attack?

The type of mining equipment is also a factor, as ASIC-secured mining networks are less vulnerable than those that can be mined with GPUs; they are much faster. Cloud services such as NiceHash—which considers itself a “hash-power broker”—theoretically make it possible to launch a 51% attack using only rented hash power, especially against smaller, GPU-only networks.

Bitcoin Gold has been a common target for attackers because it is a smaller cryptocurrency by hashrate. Since June 2019, the Michigan Institute for Technology’s Digital Currency Initiative has detected, observed, or been notified of more than 40 51% attacks—also called chain reorganizations, or reorgs—on Bitcoin Gold, Litecoin, and other smaller cryptocurrencies.

What Is Artificial Intelligence (AI)?

Artificial intelligence (AI) refers to the simulation of human intelligence by software-coded heuristics. Nowadays this code is prevalent in everything from cloud-based, enterprise applications to consumer apps and even embedded firmware.

The year 2022 brought AI into the mainstream through widespread familiarity with applications of Generative Pre-Training Transformer. The most popular application is OpenAI’s ChatGPT. The widespread fascination with ChatGPT made it synonymous with AI in the minds of most consumers. However, it represents only a small portion of the ways that AI technology is being used today.

The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal. A subset of artificial intelligence is machine learning (ML), which refers to the concept that computer programs can automatically learn from and adapt to new data without being assisted by humans. Deep learning techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.

Understanding Artificial Intelligence (AI)

When most people hear the term artificial intelligence, the first thing they usually think of is robots. That’s because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth.

Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include mimicking human cognitive activity. Researchers and developers in the field are making surprisingly rapid strides in mimicking activities such as learning, reasoning, and perception, to the extent that these can be concretely defined. Some believe that innovators may soon be able to develop systems that exceed the capacity of humans to learn or reason out any subject. But others remain skeptical because all cognitive activity is laced with value judgments that are subject to human experience.

As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optical character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function.

AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based on mathematics, computer science, linguistics, psychology, and more.

Applications of Artificial Intelligence

The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries. AI is being tested and used in the healthcare industry for suggesting drug dosages, identifying treatments, and for aiding in surgical procedures in the operating room.

Other examples of machines with artificial intelligence include computers that play chess and self-driving cars. Each of these machines must weigh the consequences of any action they take, as each action will impact the end result. In chess, the end result is winning the game. For self-driving cars, the computer system must account for all external data and compute it to act in a way that prevents a collision.

Artificial intelligence also has applications in the financial industry, where it is used to detect and flag activity in banking and finance such as unusual debit card usage and large account deposits—all of which help a bank’s fraud department. Applications for AI are also being used to help streamline and make trading easier. This is done by making supply, demand, and pricing of securities easier to estimate.

Types of Artificial Intelligence

Artificial intelligence can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon’s Alexa and Apple’s Siri. You ask the assistant a question, and it answers it for you.

Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.

Special Considerations

Since its beginning, artificial intelligence has come under scrutiny from scientists and the public alike. One common theme is the idea that machines will become so highly developed that humans will not be able to keep up and they will take off on their own, redesigning themselves at an exponential rate.

Another is that machines can hack into people’s privacy and even be weaponized. Other arguments debate the ethics of artificial intelligence and whether intelligent systems such as robots should be treated with the same rights as humans.

Self-driving cars have been fairly controversial as their machines tend to be designed for the lowest possible risk and the least casualties. If presented with a scenario of colliding with one person or another at the same time, these cars would calculate the option that would cause the least amount of damage.

Another contentious issue many people have with artificial intelligence is how it may affect human employment. With many industries looking to automate certain jobs through the use of intelligent machinery, there is a concern that people would be pushed out of the workforce. Self-driving cars may remove the need for taxis and car-share programs, while manufacturers may easily replace human labor with machines, making people’s skills obsolete.

What Is the Asia-Pacific Economic Cooperation (APEC)?

The Asia-Pacific Economic Cooperation (APEC) is an economic group of 21 members, formed in 1989, with the primary goal of promoting free trade and sustainable development in the Pacific Rim economies.

Understanding the Asia-Pacific Economic Cooperation (APEC)

APEC’s principal goal is to ensure that goods, services, capital, and labor can move easily across borders. This includes increasing custom efficiency at borders, encouraging favorable business climates within member economies, and harmonizing regulations and policies across the region.

The creation of APEC was primarily in response to the increasing interdependence of Asia-Pacific economies. The formation of APEC was part of the proliferation of regional economic blocs in the late 20th century, such as the European Union (EU) and the (now-defunct) North American Free Trade Agreement (NAFTA).

Nations Comprising APEC

The founding members of APEC were Australia, Brunei, Canada, Indonesia, Japan, Korea, Malaysia, New Zealand, the Philippines, Singapore, Thailand, and the U.S. Since its launch, China, Hong Kong, Taiwan, Mexico, Papua New Guinea, Chile, Peru, Russia, and Vietnam have joined its ranks.

APEC refers to its members as economies rather than as states due to the focus on trade and economic issues rather than the sometimes delicate diplomatic issues of the region, including the status of Taiwan and Hong Kong. The People’s Republic of China (PRC) refuses to recognize Taiwan because it claims the island as a province under its constitution. Hong Kong, meanwhile, functions as semi-autonomous regions of China and not a sovereign state.

Official observers of APEC include the Association of Southeast Asian Nations (ASEAN), the Pacific Economic Cooperation Council (PECC), and the Pacific Islands Forum (PIF).

The Asia-Pacific Economic Cooperation’s (APEC) Actions and Goals

At a landmark summit meeting in 1994, APEC announced a lofty goal of establishing free trade and investment regimes in the Asia-Pacific region by 2010 for members with developed economies. The group hoped to achieve those same goals for its developing economy members by 2020.

In 1995, APEC adopted the Osaka Action Agenda, a program designed to facilitate business activities, liberalize trade and investment and promote economic and technical cooperation. However, progress on these efforts has somewhat slowed, due to APEC’s culture of making all decisions by consensus. While some decisions are unanimous, they are not legally binding on the member governments.

Sub-Groups of APEC

APEC maintains a policy support unit to provide research and analysis to support the organization’s goals for the region, as well as special working groups to explore and promote various issues and components of economic development. These groups engage in multiple micro causes that aim to advance policy and awareness. Examples of these sub-groups include:

• Gender Issues: APEC sponsors a policy partnership on women and the economy to advance the economic integration of women. An estimated 600 million women are currently in the region’s labor force.
• Intellectual Property Rights: APEC’s Intellectual Property Rights Experts’ Group (IPEG) studies and exchanges information regarding the enforcement of intellectual property rights protections in the region. It promotes and facilitates cooperation to implement the World Trade Organization’s (WTO) Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS).
• Emergency Preparedness: APEC’s Emergency Preparedness Working Group (EPWG) promotes business resilience, public-private partnerships, and information sharing among members to help build the region’s capacity to deal with emergencies and natural disasters. Economies along the geologically and climatologically active Pacific Rim are subject to events such as tsunamis, typhoons, earthquakes, and volcanic eruptions.