Altcoin Roundup: Holding Bitcoin? Heres how to put it to work in DeFi – Cointelegraph

The long-awaited day finally came on Oct. 19 as the first Bitcoin (BTC) exchange-traded fund (ETF) went live on the New York Stock Exchange, thrusting the crypto asset into the limelight across mainstream news outlets and alternative media alike.

Despite the fact that the ETF in question will hold no actual Bitcoin and is instead a futures-based instrument, investors and pundits across the ecosystem have largely hailed its launch as proof that Bitcoin has hit the big leagues and will soon surpass the coveted $100,000 price target.

Many investors either dont have access or will choose not to interact with the newly launched EFT, but holders can still use a variety of strategies to earn a yield on their BTC holdings.

Heres a look at some strategies BTC holders can use to earn a yield.

BadgerDAO is an open-source protocol built on the Ethereum network that has the specific goal of building products and the required infrastructure needed to simplify the integration of Bitcoin into decentralized finance (DeFi).

Currently, BadgerDAO has the most extensive list of BTC paired pools where investors can provide liquidity.

As seen in the image above from the BadgerDAO dashboard, there are different offerings from the simple staking of Wrapped BTC (wBTC), which can earn a yield ranging from 1.22% to 27.98% depending on the terms of the lockup, to the staking in more complex liquidity provider (LP) strategies like the renBTC/wBTC/sBTC pool, which offers a yield ranging from 7.07% to 45.37%.

It is important to note that there are risks involved with wrapping BTC and RenVM because a user must relinquish control of the original BTC in order to obtain either wBTC or renBTC, violating the crypto code of not your keys, not your crypto.

For LP tokens that pair BTC with other cryptocurrencies such as Ether (ETH), BADGER or stablecoins like Tether (USDT) and USD Coin (USDC), holders must also consider the possibility of suffering an impermanent loss if the price of Bitcoin increases by a significant amount compared to the other token it is paired with.

Trader Joe is the largest decentralized trading platform by total value locked (TVL) on the Avalanche network, according to data from Defi Llama, with $2.18 billion worth of assets currently on the protocol.

Using wBTC on the Avalanche Network requires another layer of wrapping that produces wBTC.e, which can then be traded on the network or used to provide liquidity.

At the time of writing, Trader Joe is offering a yield on three LP tokens, including a return of 26.223% for the wBTC.e/AVAX pair, 16% for the wBTC.e/USDC.e pair, and 11.9% for the wBTC.e/USDT.e pair. All rewards are paid out in the protocols native JOE token.

Raydium is the top-ranked DeFi protocol on the Solana network, according to data from Defi Llama, and currently boasts a TVL of $1.77 billion.

Users who wish to use their BTC on Solana have the option of pairing it with USDC, USDT, Serum (SRM) and a wrapped form of Solana known as mSOL.

The yields offered range from 5.16% to a high of 14.27%, with all rewards paid out in the platforms native RAY token.

PancakeSwap is the No. 1 ranked protocol by TVL on the Binance Smart Chain (BSC) with data from Defi Llama showing that $5.39 billion worth of tokens is currently locked on the protocol.

In order to utilize Bitcoin on the BSC, it must first be wrapped to become BTCB, which can then transact on the network.

At present, PancakeSwap is offering a 5.44% return for the BTCB/ETH pair, a 15.82% return for the BTCB/BUSD pair (Binances stablecoin, Binance USD) and 20.79% for the BTCB/BNB pair. All rewards are paid out in the protocols native CAKE token.

Related: Valkyrie Bitcoin futures-linked ETF launches on Nasdaq, with share prices dropping 3% in first hour

DYdX is a decentralized perpetual futures trading platform that made waves back in September when it airdropped thousands of dollars worth of its native DYDX governance token to early adopters of the platform.

Similar to the ProShares Bitcoin Strategy ETF, trades made on the dYdX protocol do not settle in actual Bitcoin but instead in a USD stablecoin, so BTC stakers may not be too interested in the protocol if directly increasing Bitcoin holdings is the only goal.

However, as opposed to trading a government-regulated futures product that is only available when the traditional markets are open, dYdX offers the decentralized, 24/7 trading environment that the crypto faithful have grown to love.

The views and opinions expressed here are solely those of the author and do not necessarily reflect the views of Cointelegraph.com. Every investment and trading move involves risk, you should conduct your own research when making a decision.

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Altcoin Roundup: Holding Bitcoin? Heres how to put it to work in DeFi - Cointelegraph

Ethereum: the transformation that could see it overtake bitcoin – The Conversation UK

The worlds second most valuable cryptocurrency, ether, has been touching all-time highs in price ahead of a major upgrade of its underlying platform, ethereum. Ether is currently worth in aggregate just shy of US$500 billion (363 billion). Thats still slightly less than half that of the biggest cryptocurrency, bitcoin.

But could this upgrade, a vital step towards a much greener and faster version of the current system, put ethereum on the path to becoming the dominant platform on the internet and make ether number one?

First of all, its important to understand the difference between bitcoin and ethereum. Bitcoin is a system for allowing people to send value between one another without the need for banks. It is built on a technology known as blockchains, which are online ledgers whose transactions are checked and recorded by a decentralised network of computers known as validators.

These validators are incentivised for their work by receiving newly minted bitcoin as rewards, in what is known as mining. To make this more attractive, bitcoin is relatively scarce: only around 18 million coins are in existence and the protocol is such that there can never be more than 21 million.

Ether vs bitcoin by total value (market cap)

Ether works in a similar way to bitcoin, but ethereum is different. It is a worldwide software platform with no host, on which developers are building thousands of blockchain-based applications.

This means these applications can all run without being controlled by a company. Examples include cryptocurrency exchanges, insurance systems, and new kinds of gaming.

At the heart of the platform is the idea of smart contracts, which are automated agreements that ensure that money and assets change hands when certain conditions have been fulfilled. All transactions on the platform ultimately use ether, and the success of the platform is why ether has been the second-largest cryptocurrency after bitcoin for the past few years. The fact that ether fuels the platform even being referred to as gas fees gives it a utility and an intrinsic value that bitcoin does not have.

Ethereum has several major problems, however. The first is that gas fees have become very expensive in the last couple of years because the network has become so popular and is therefore very congested.

Validators prioritise users who are willing to pay the highest fees for their transactions. For example, the average transaction at the time of writing on crypto exchange Uniswap costs around US$44 in gas fees.

Bitcoin has comparable issues with congestion, which its developers are trying to solve by building applications like Lightning on top which boast faster transaction speeds.

The second problem for ethereum is that, as it has become more popular, the amount of computational power used by validators has rocketed. Its the same problem that has brought a lot of negative publicity to bitcoin, because it uses a lot of electricity.

Bitcoin is currently using as much power as the whole of the Philippines, although its supporters argue that much of this is power that would otherwise be wasted for example, oil rigs burning off natural gas because its not profitable to sell it. Proponents also point out that the network is shifting towards using much more renewable power over time.

At any rate, the eventual creation of an ethereum 2.0 will solve these problems by moving the platforms system of validation from proof of work to proof of stake. Without getting into too many details, proof of work is a protocol in which validators all attempt to solve complex equations to prove that each proposed transaction is valid. With proof of stake, theres no need for all validators to do this power-hungry work, because the system chooses one at random to confirm each transaction.

Many in the bitcoin community are against proof of stake because it gives the most power to the biggest validators, potentially allowing them to corrupt the system of validation if they can get control of more than half of the network. Ethereum supporters counter that proof of stake has checks and balances built in that would prevent this from happening.

Either way, ethereum 2.0 promises to reduce the platforms power consumption by 99.9%, making it far more sustainable. It should also solve the problem with gas fees by raising the platforms processing ability from 30 transactions a second to potentially 100,000, as well as making possible more sophisticated smart contracts than before.

The transition to ethereum 2.0 has been a slow one, riddled with technical issues that have dragged on for over two years. For the past few months, the new proof-of-stake blockchain has been running in a test format in parallel with the existing system, allowing the developers to prepare it for a merger in 2022.

The forthcoming upgrade is essentially a warm up for this merger. Known as Altair, it introduces numerous technical changes that are designed to keep validators honest and make the system more decentralised. Assuming this goes ahead as planned, all eyes will be on the merger, and then later another change known as sharding which will greatly increase the systems processing capability.

Certainly the price of ether has been strong ahead of the Altair upgrade. The recent surge in bitcoin to all-time highs has been helping to lift the entire crypto market. But some of the price movement in ether probably reflects people betting that the upgrade will succeed, while the rest is from speculators switching from bitcoin, and new money moving into the space.

Ether vs the eth killers by total value

In the run-up to the merger of ethereums two blockchains, it will be interesting to see how all this affects ethers price in relation to the so-called eth killers. These are rival platforms like cardano and solana that have been very popular in recent months partly due to ethereums problems with fees.

But ultimately the question is what it will mean for bitcoin. Bitcoiners will continue to argue that their protocol is more decentralised than proof of stake, and they have the advantage of being the crypto brand that investors are most comfortable risking their money with.

The question is whether these advantages are outweighed by ethereum 2.0s greener credentials and the fact that it can handle more transactions. Bitcoin is currently worth about double ether, but talk comes and goes about a flippening where ether overtakes it. Could it happen in 2022? With bitcoins hegemony at stake, it will be fascinating to find out.

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Ethereum: the transformation that could see it overtake bitcoin - The Conversation UK

Bitcoin sees its highest ever daily close as BTC/Euro pair hits all-time highs – Cointelegraph

Bitcoin (BTC) failed to beat its all-time highs on Oct. 20, but a separate record kept bulls confident of a breakout.

Data from Cointelegraph Markets Pro and TradingViewshowed BTC/USD reaching $64,490 on Bitstamp overnight.

While inches from matching Aprils peak, the action nonetheless sealed Bitcoins highest-ever daily close around $64,230.

In several currencies, including the Japanese yen, Australian dollar and euro, new all-time highs were already in on Wednesday.

For popular trader Crypto Ed, it was time to reevaluate likely short-term targets.

Summary: at 40k I mentioned 73k as first target but I think were going higher and keep extending those waves. I think we even have a good chance were not going sub 60k for a while, he tweeted.

A worst-case scenario could involve a brief spike downward to $58,000, but this would be followed by clear skies for the coming weeks/ months, he added.

The bullish tone across the board follows a successful day for the first Bitcoin exchange-traded fund (ETF) in the United States, with $1 billion in volume and $550 million in assets under management after just a single trading session.

Correspondingly, Bitcoin futures open interest hit fresh all-time highs of $817.6 million, data from on-chain analytics firm Glassnode confirms.

The atmosphere makes the comparative lack of mainstream interest in Bitcoin all the more unusual.

Related:Bitcoin RSI strength suggests BTC price is still far from its cycle top

Beyond institutional excitement, data shows that hardly anyone is following or checking on Bitcoin relative to earlier this year.

As Cointelegraph reported, this has been the case for some time, but even a trip to the threshold of all-time highs has failed to upend the trend.

A normalized score from Google Trends put Bitcoin interest at 36 this week, relative to 100 in mid-May.

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Bitcoin sees its highest ever daily close as BTC/Euro pair hits all-time highs - Cointelegraph

The Roads To Hyperbitcoinization – Bitcoin Magazine

Introduction

The widespread adoption of bitcoin is a topic that has raised immense expectations for change to monetary systems, governments, and society in general. Over the years, bitcoiners have fiercely defended their belief that bitcoin represents a superior form of money and expressed a large number of hypotheses about possible pathways to the broader adoption of bitcoin. Over the years, Bitcoiners have fiercely defended their belief that bitcoin represents a superior form of money and expressed a large number of hypotheses about possible pathways to the broader adoption of bitcoin. In this article, we investigate the concept of hyperbitcoinization which represents one of the most promising potential developments of our time. By hyperbitcoinization, we mean the process of rapid and irreversible adoption of bitcoin as the primary global monetary reserve.

This article is part of a longer series wherein we outline the views and predictions made by the bitcoin community concerning the prospect of hyperbitcoinization. In our analysis we highlight "transition agents," i.e., main players, groups of players, or institutions that could accelerate the transition to a bitcoin world. For each topic, we base our arguments on the references collected, and if possible, present data that aims to verify the probability of this outcome. This first article describes top-down scenarios initiated by institutional agents or governments whose influence is expected to trickle down to a wider audience, while a second article will provide an understanding of bottom-up types of initiatives.

The views presented in this article are intended to capture the pulse of the Bitcoin community and remain hypothetical. This is an initial foray into analyzing hypothesized hyperbitcoinization scenarios; we expect that this area will require on-going investigation.

The informational resources that most accurately reflect the extent of bitcoin adoption are often private and/or anonymous, but a significant part of the sentiment is publicly available. The methodology employed in this study can be broken down into four steps: collection, content analysis, validation/extrapolation, and convergence.

Step 1: Collection

With the aim of identifying agents of transition that may initiate a hyperbitcoinization scenario, we conducted online research of articles, blog posts, podcasts, videos, data sets, tweet samples and research papers from July 2013 to July 2021 that either contained the term hyperbitcoinization or referenced the rapid adoption of bitcoin:

Figure 1. Frequency of hyperbitcoinization in online materials.

Step 2: Analysis

Through analysis of the articles and transcripts of the videos/podcasts we identified recurring themes highlighting the current social, political, and monetary contexts, the agents or events engendering the transition to the bitcoin world, and only a few projections about the prospect of a hyperbitcoinized world.

Step 3: Validation/Extrapolation

Qualitative data collected in step 1 most often came in the form of predictions discussed within the bitcoin community that have yet to be subjected to critical examination by the wider financial and economic communities. In the following section we present a quantitative analysis that critically examines these hypothesized causal pathways by using micro and macroeconomic data from government, institutional, and public databases to extrapolate the feasibility of such scenarios.

Step 4: Convergence

In the last step, we coded each reference to hyperbitcoinization according to a descriptive theme so that we might present a coherent overview of the current discussion within the Bitcoin community. Despite the great diversity of authors, the analysis that follows shows that hyperbitcoinization predictions converge on a limited number of cases where the transition is triggered by four main groups of actors. These four groups who may influence hyperbitcoinization include central banks, governments, the private sphere, and the Bitcoin community.

The financial and economic worlds, crystallized in the fiat system for the last several decades, are unable to perceive credible alternatives to their current reality. According to current economic and financial elites, a different monetary system based on the gold standard or the bitcoin standard would give rise to an anarchic and violent society wherein all concepts of law, economics, or civilization would disappear. Bitcoiners, on the other hand, offer a more optimistic narrative (Keiser and Seiche 2021). Inspired by libertarian thought, they see the government as a superfluous or useless element of society whose interventionism in the monetary field prevents the proper functioning of the market. In this view, the advent of bitcoin would restore monetary stability based on the fixed and transparent production of money.

Figure 2. Hyperbitcoinization scenarios driven by central banks.

Central Banks

Inflation of Money Supply

Out of all the hypotheses made by Bitcoin community members, the most frequent reason cited as a possible trigger for hyperbitcoinization centers on money manipulation by central banks. At several points in history, monetary inflation set off a vicious cycle of decreased purchasing power that culminated in a complete loss of faith in the currency under inflationary pressure. In figure 3, we rank countries based on an annualized increase in broad money between the years 20152020.

Figure 3. Annualized monetary inflation (CAGR period 20152020). The World Bank. 2021. Broad Money (Current LCU). Washington, D.C.: The World Bank. https://data.worldbank.org/indicator/FM.LBL.BMNY.CN.

Unsurprisingly, figure 3 shows that a large number of countries from this sample suffer from aggressive interventionism with yearly increases of monetary supply higher than 10%. For instance, a 10% annual increase of the money supply implies a decrease in purchasing power of 40% after only five years. The stability and predictability of bitcoin supply has the potential to disrupt the vicious cycle of manipulated monies leading to the loss of faith in the manipulated currency, and elicit the interest of the general population in the hardest form of money ever invented.

Central Bank Digital Currencies

The imminent launch of CBDCs (Central Bank Digital Currencies) by several countries will undoubtedly impact the cryptocurrency industry, but it is not completely clear how this intervention will unravel. Initially we can expect central governments to nudge their populations toward CBDCs through large-scale educational campaigns that will likely have a collateral effect on bitcoin adoption. However, as the limits of centrally-governed monies emerge, we can predict this will push new users into Bitcoins arms for at least four of the following reasons:

Government

One of the most common hyperbitcoinization hypotheses is the adoption of bitcoin initiated by governments. Figure 4 describes several prospective scenarios hypothesized by the Bitcoin community that have yet to occur.

Figure 4. Hyperbitcoinization scenarios driven by governments.

State Hoarding Of Bitcoin Scenario

In this scenario, the transition toward a bitcoin standard unfolds in distinct ways whether we look at it from the angle of individuals or governments. In Layered Money, Nik Bhatia (2021) predicts that governments will progressively build a healthier monetary system on top of the hardest money ever created: bitcoin.

Figure 5. Nik Bhatia. 2021. Layered Money: From Gold and Dollars to Bitcoin and Central Bank Digital Currencies. Nikhil Bhatia.

Several countries have reported possession of bitcoin after seizing it from criminal activities, but no country has announced a specific strategy for hoarding digital assets as a reserve currency. In this context, El Salvador is an outlier in adopting bitcoin. The acceptance of bitcoin as a legal tender in El Salvador could be interpreted as an isolated political decision, but the successive announcements by the government to first implement a national mining policy with the BigBlock Datacenter and subsequently to hoard BTC, confirm the execution of a broader bitcoin strategy in the country.

Sputnik Trade Scenario

For decades, the dollar's status as a global reserve currency has given the U.S. the privilege to impose sanctions on a global scale (figure 6).

Figure 6. Map of countries sanctioned by U.S. Wikimedia.org, JojotoRudess, CC BY-SA 4.0 , via Wikimedia Commons.

Predictions about the demise of the hegemonic dollar are not new, but recently new narratives have appeared speculating on how the adoption of bitcoin could contribute to the decline of the U.S. dollar (Clemente 2021). If two countries suffering under U.S. sanctions start using bitcoin as a settlement layer to circumvent these sanctions, doing so may provide the same kind of rude awakening for world governments as Sputnik had for U.S. space policy in the 1960s. From that point, it could set an alternative path for other countries to replicate. Iran, whose economy has been under embargo since 1979, sits on a large reserve of fossil fuel energy that could either be exported against a payment in bitcoin or by selling hashrate. The Iranian currency could become one of the most sought after global currencies and reposition the country on the pedestal of sound money (Keiser and Seiche 2021).

El Salvador Case

The announcement made by the president of El Salvador to accept Bitcoin as legal tender was greeted as a consecration by the Bitcoin community in the word. El Salvador, whose economy has been hit hard by the Covid-19 pandemic, has long dealt with high crime rates linked to drug trafficking. The countrys dependence on the U.S. is high both in terms of exports and expatriate remittances (figure 7).

Figure 7. Total cost of transaction for remittance of $200 based on World Bank data. World Bank, Remittance Prices Worldwide, available at remittanceprices.worldbank.org,

The bill proposed by President Nayib Bukele to the legislative assembly aims to position the country on the rails of prosperity by creating job opportunities, driving more inclusion, and boosting the economy. Even if this bill created a lot of excitement among Bitcoiners, forced money law in this case bitcoin as a legal tender diverges from the Bitcoin communitys central values of freedom, voluntarism, and free competition (Koning 2021).

This initiative provoked mixed reactions from global financial institutions. As expected, the International Monetary Fund expressed serious concern about the adoption of bitcoin as legal tender by the Central American country and pronounced that the bill presented a number of macroeconomic, financial, and legal risks. The Central American Bank for Economic Integration (CABEI), whose mission is to promote the economic integration and social development of the Central American region, took a more constructive and pragmatic approach. They offered technical assistance to the country to help with the implementation of the new system.

Since the announcement of the bill, officials from Paraguay, Panama, and Mexico have expressed their intentions to present crypto-related bills in the coming months to duplicate the process initiated by President Bukele.

If the experience in El Salvador, whose dependence on remittances is estimated at 24% of Gross Domestic Product, translates into an improvement in economic conditions, many countries beyond Central America could be incentivized to follow the same path as shown on the following map:

Figure 8. World Bank staff estimates of personal remittance received (% GDP) for Africa & Asia based on IMF balance of payments data, and World Bank and OECD GDP estimates.

On an exploratory basis, we estimated the impact on countries GDP if current remittance solutions are replaced by Lightning Network (LN) payments. As part of this estimate, we assumed a zero cost LN transaction and remittance cost equivalent to the average observed for transactions of $200 in each country. Figure 9 shows that the economic impact would be particularly beneficial for countries whose dependence on foreign capital inflows is greater than 20%.

Figure 9. World Bank staff estimates of the impact of zero-cost transactions on country GDP (%) based on IMF balance of payments data, and World Bank and OECD GDP estimates.

This study synthesized hyperbitcoinization scenarios and identified key agents that may initiate this transition. We categorized these scenarios into two groups: (1) top-down initiatives stemming from institutional actors such as central banks and governments, and (2) bottom-up initiatives emerging from the private sphere and Bitcoin communities. This first article presented an exhaustive analysis of the top-down scenarios, however the current state of adoption of Bitcoin technology does not permit drawing definitive conclusions about the influence of a particular agent. Rather this article serves as a foundational framework to continue our analysis of these prospective scenarios over time. The decentralized nature of Bitcoin is often in tension with the priorities of governments and financial organizations which are centralized, but this study shows how these institutions may play a major role intentionally or unintentionally in a mass adoption of bitcoin.

In a second article, we will present bottom-up scenarios driven by private and individual actors as a comparison to the top-down pathways.

This is a guest post by Alexandre Bussutil. Opinions expressed are entirely their own and do not necessarily reflect those of BTC, Inc. or Bitcoin Magazine.

Bibliography

Alden, L., & Posch, A. (Aug 6, 2020). Lyn Alden Bullish On Bitcoin A Strategic Value Investors View https://www.youtube.com/watch?v=_D-11qqH4cM

Clemente III, W. (Jan 24, 2021). Hyperbitcoinization. The Path To Becoming The Worlds Dominant Form Of Money https://www.bitrawr.com/hyperbitcoinization

Fan, Y. (April 1, 2020). Some Thoughts On CBDC Operations In China https://www.centralbanking.com/fintech/cbdc/7511376/some-thoughts-on-cbdc-operations-in-china

Keiser, M., & Seiche, L. (Jan 8, 2021). ES MCCVR 2020: Max Keiser & Lina Seiche - Hyperbitcoinization: Maximalist Utopia or Inevitable Endgame? https://www.youtube.com/watch?v=kese9tMFgvc

Koning, J. (June 16, 2021). Hyperbitcoinization: By Choice or by Force? American Research for Economic Research. https://www.aier.org/article/hyperbitcoinization-by-choice-or-by-force/

Minting Coins. (Sept 9, 2017) #88 Hyperbitcoinization + SEC Meeting, Overstock, Google, & Byzantium Metropolis youtube.com. https://www.youtube.com/watch?v=PgjmSGjjRvo

Redman, J. (April 6, 2020). Hyperbitcoinization: Visions of Bitcoin Fueling the Post Covid-19 Shadow Economy https://news.bitcoin.com/hyperbitcoinization-post-covid-19-shadow-economy/

Suberg, W., & Draper, T. (March 3, 2021). Netflix 'Might' Be Next Fortune 100 Firm To Buy Bitcoin Tim Draperhttps://cointelegraph.com/news/netflix-might-be-next-fortune-100-firm-to-buy-bitcoin-tim-draper

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The Roads To Hyperbitcoinization - Bitcoin Magazine

As the Crypto Economy Nears $3 Trillion, Top 10 Crypto Exchanges Hold Over $206B, More Than 7% Economics Bitcoin News – Bitcoin News

The crypto economy has come awfully close to nearing the $3 trillion handle as far as the value of all 10,000+ crypto assets is concerned. Today, crypto market aggregation sites show the entire crypto-economy at $2.756 trillion is worth more than the value of Apples market cap at $2.467. Furthermore, the top ten crypto-asset exchanges, in terms of cryptocurrencies held in reserves, hold more than $200 billion or 7.47% of the entire crypto economy.

Digital currencies are far more valuable today than they were a month ago and the crypto economy is coming close to topping $3 trillion in value. The whole crypto-economy surpassed Apples overall worth this past week as bitcoin (BTC) became the sixth-most valuable asset on earth and ethereum (ETH) is now the 15th-largest global asset. While BTC has a $1.2 trillion market cap, ETH commands a market valuation of over $500 billion.

Meanwhile, the top ten crypto asset trading platforms, in terms of cryptocurrencies held in reserves, hold 7.47% of the entire crypto-economy under custody. The top ten crypto asset exchanges that hold the most value in crypto assets in custody are Coinbase, Binance, Huobi Global, Kraken, Okex, Gemini, Bitfinex, Bittrex, Bitmex, and Bitflyer respectively. All ten of these exchanges on Thursday, October 21, 2021, hold approximately $206.263 billion using todays exchange rates.

The Exchange Transparent Balance Rank data on Thursday is provided by Bituniverse with help from Peckshield, Etherscan, and Chain.info. Out of the whopping $206 billion held on centralized exchanges, Coinbase holds 35.84% with $73.84 billion held in reserves. Binance holds 14.78% of the $206 billion with $30.46 billion. Both Bitmex and Bitflyer hold the least amount of crypto reserves in the top ten positions, with Bitmex holding $7.27 billion and Bitflyer holding $4.89 billion in crypto reserves.

All ten of these exchanges combined hold more value than the overall market capitalization of Fortune 500 companies like Comcast, Pfizer, Cisco, Coca-Cola, and Intel. Its safe to say that the top ten crypto exchanges in terms of crypto reserves held in custody are becoming heavyweight behemoths in the world of finance, thanks to the growing value of the crypto economy.

What do you think about the top ten crypto exchanges holding $206 billion in cryptocurrencies? Let us know what you think about this subject in the comments section below.

Image Credits: Shutterstock, Pixabay, Wiki Commons

Disclaimer: This article is for informational purposes only. It is not a direct offer or solicitation of an offer to buy or sell, or a recommendation or endorsement of any products, services, or companies. Bitcoin.com does not provide investment, tax, legal, or accounting advice. Neither the company nor the author is responsible, directly or indirectly, for any damage or loss caused or alleged to be caused by or in connection with the use of or reliance on any content, goods or services mentioned in this article.

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As the Crypto Economy Nears $3 Trillion, Top 10 Crypto Exchanges Hold Over $206B, More Than 7% Economics Bitcoin News - Bitcoin News

Much-anticipated bitcoin futures ETF makes its debut on the NYSE: CNBC After Hours – CNBC

CNBC.com's Pippa Stevens brings you the day's top business news headlines. On today's show, CNBC.com's Tanaya Macheel reports on the first U.S. bitcoin ETF, which popped on its first day of trading. Plus, Netflix posts better-than-expected subscriber growth in the third quarter.

Shares of the first U.S. bitcoin-linked exchange-traded fund rose in their trading debut Tuesday.

TheProShares Bitcoin Strategy ETF, ticker "BITO," jumped 4.8% to close at $41.94. The fund tracks CME bitcoin futures, or contracts speculating on the future price of bitcoin, rather than the crypto itself.

That means investors in the ETF should expect the price and performance of the shares to differ somewhat from the price of bitcoin itself. This isn't ideal for existing investors; many of them take a long view on cryptocurrencies and had hoped for an ETF that would track physical bitcoin that investors could buy and hold.

The price ofbitcoinjumped more than 4% Tuesday to $64,206.51, according to Coin Metrics, about 1% from its all-time high from April 14 of $64,899. Bitcoin futures gained about 4% as well.

The launch highlights the remarkable growth of the ETF industry, Will Hershey, CEO of Roundhill Investments, told CNBC.

Netflixshares were up slightly after-the-bell Tuesday after the company postedthird quarter results, showing investors the streamer can continue to attract new subscribers.

The quarter's subscriber growth of 4.4 million was a solid beat over the expected 3.84 million. Analysts had expected users to flock to the streamer as it began to roll out a slew of content that was delayed to the back half of the year due to the pandemic.

The company said it expects to add 8.5 million subscribers in the fourth quarter. Netflix added it plans to have a more normal release schedule over the course of 2022, barring any Covid-related delays.

Securities and Exchange Commission ChairmanGary Genslersaid Tuesday that Wall Street's top regulator is working to determine if payment for order flow needs to be reformed or barred to ensure a competitive marketplace for buying and selling trading volume.

Gensler acknowledge that modern agreements between brokers and market makers have made trading far cheaper and efficient than in prior decades, but noted that some troubling conflicts of interest remain.

"Our markets have moved to zero commission, but it doesn't mean it's free. There's still payment underneath these applications. And it doesn't mean it's always best execution," the SEC chief said on CNBC's "Squawk on the Street."

Online brokerages that tout "free" or zero-commission trading typically make money by selling their customers' orders to high-frequency market makers who execute the buying and selling. That process is controversial and known on Wall Street as payment for order flow.

Continued here:
Much-anticipated bitcoin futures ETF makes its debut on the NYSE: CNBC After Hours - CNBC

This Bitcoin Chart Is Like a Cheat Code for Calling Top Cryptocurrencys Trajectory, Says C… – The Daily Hodl

A closely followed strategist is eyeing price charts from the 2017 Bitcoin (BTC) bull run to see where the worlds leading crypto is heading next.

Justin Bennett tells his 82,800 Twitter followers that comparing BTCs previous peaks and valleys is like having a cheat code. He foresees a new all-time high of $80,000 just around the corner, followed by a leap past $100,000.

The 2017 fractal accounts for this weeks pullback.

Each move this cycle has been a little less aggressive than in 2017.

It was a 13% pullback then. Probably an 8-10% pullback now, or $60k BTC.

Then $80k+ in early November, $65k retest in mid-November, and $100k+ in December.

The trader uses some video game jargon in a follow-up tweet.

This is like having a cheat code

As long as it doesnt deviate.

Bennett next zooms in on the BTC candles chart as he highlights a pullback that mirrors a 2017 price drop.

Heres that slight BTC pullback I was referring to yesterday.

Next area of support is $58,000 $60,000.

Bitcoin needs to reclaim the $64,000 area to become constructive again.

Finally, the analyst plots out a price road map where Bitcoin surges well past $100,000 into the $200,000+ range by early January of next year.

I think something like this is much more likely.

Featured Image: Shutterstock/sezer66

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This Bitcoin Chart Is Like a Cheat Code for Calling Top Cryptocurrencys Trajectory, Says C... - The Daily Hodl

We Need to Protect American Innovation in the Competition with China | Opinion – Newsweek

America's technology sector produces the world's most innovative and successful companies. Yet there's a near-bipartisan consensus in Washington that the days of "Big Tech"companies like Google, Facebook and Microsoft, which have made a number of high-profile acquisitionsmust come to an end.

Liberals seek to rein in the supposed excesses of technology companies when it comes to wages and workers' rights, while conservatives rant about censorship and deplatforming on Twitter. Meanwhile, America's adversaries in the Xi Jinping government in Chinaa rising superpower that cheats and steals its way to victorychuckle at our self-destructive response. Rather than enhancing our innovative technology industry, we risk undermining it through increased government intervention.

The United States is home to companies that make up substantially more than half of the market value of the top 100 global public companies. Technology makes up more than a third of America's contribution to that market value, at nearly $8 trillion. According to the World Bank, the innovation-based digital economy grew more than twice as fast as the overall GDP between 2004 and 2019. In the U.S., the digital economy has grown more than three times as fast as the overall U.S. economy since 2005. This torrid growth increases domestic employment and labor productivity. All of this redounds directly to U.S. national securityeconomic security is national security.

America's economic future depends not on big manufacturing, but on technology and innovation. Where steel plants and manufacturing plants once stood, we now see software development and chip design labs, cloud computing nodes and supply distribution centers. All this has happened specifically in the United States precisely because the government allowed resources to flow to their most productive uses and at times helped prime the pump with basic research funding.

The U.S., unlike some European nations, has avoided creating a vast web of bureaucracy and heavy-handed government regulation. While there are some pockets of innovation in Europe, the regulatory environments in France, Germany and Spain make them much less attractive to cutting-edge companies. Venture capital investment in the U.S. is more than three times larger than in the EU. For all of its foibles, America remains a good bet for innovative companies.

Our relatively laissez-faire economic policy has also created a robust startup community. It supports strong venture capital funding, like Andreessen Horowitz' investments in the burgeoning crypto industry and social media app Clubhouse. It also has helped the U.S. become the world leader in startup acquisitions.

Current U.S. economic policy has also created long-term growth opportunities in the public markets. American tech companies, for example, make up four of the five most valuable public companies based on market capitalization. Larger technology companies like Illumina may very well be able to fund smaller ones like Grail. They can identify opportunities to leverage economies of scale, make important innovations, such as new ways to screen for cancer, and bring new technology like multi-cancer early detection tests to market. This is a good thing.

Yet today we hear increased calls for government control. These calls are motivated by concerns about the political influence of a handful of tech firms. Conservatives who want to use antitrust to punish Big Tech believe that large technology platforms have too much control over speech and are censoring those who share their views. Liberals who favor breaking up these companies worry about Big Tech's power over democracy, small business and worker rights.

But as the economic evidence shows, when companies can operate free from fear of punishment, competition flourishes and consumers benefit. Those in favor of stringent antitrust enforcement often argue that it will strengthen the small-business sector by lowering prices and increasing wages. Small businesses, however, experience many benefits from the tech sector that allow them to operate efficiently. Computing power is more affordable than ever. In the majority of technology jobs, wages are drastically higher than in other areas.

A number of failed antitrust lawsuits have exposed the weakness of the "break 'em up" movement. Recent government and private cases against Qualcomm, Facebook and Apple have failed for lack of evidence to support claims of inappropriate use of monopoly power, even as the government tries again and again. This is not surprising; antitrust law is designed to stoke competition and stop anti-competitive behavior, not to solve political disputes or kneecap successful companies.

Transforming our core business laws, as a range of legislative proposals seek to do, would be dangerous. U.S. antitrust laws have kept competition vibrant and the economy humming. Modern competition law and the consumer-welfare standard have created a stable, predictable climate for firms to innovate.

China, meanwhile, has gone down this roadto no good end. Its "crackdown" on large companies has little if anything to do with creating competition or innovation. Rather, the government's goal appears to be to punish companies that refuse to consistently toe the party line.

For now, those who want to regulate American technology seem to have the upper hand. But their victory is likely to be short-lived. Americans are increasingly attuned to the threat that China poses to our future. They recognize that if we are going to remain competitiveeither economically or militarilywe need more American (and allied) innovation now.

The American people want and need real innovation driven by entrepreneurs, not bureaucrats in Washington. We ought to let them have it.

Jamil N. Jaffer is the former Chief Counsel and Senior Advisor to the U.S. Senate Foreign Relations Committee and currently serves as the Founder and Executive Director of the National Security Institute at George Mason University's Antonin Scalia Law School. Joshua D. Wright is a former Commissioner of the Federal Trade Commission (FTC) and currently serves as the Executive Director of the Global Antitrust Institute and University Professor at George Mason University's Antonin Scalia Law School.

The views expressed in this article are the writers' own.

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We Need to Protect American Innovation in the Competition with China | Opinion - Newsweek

What is Artificial Intelligence (AI)? | Oracle

Despite AIs promise, many companies are not realizing the full potential of machine learning and other AI functions. Why? Ironically, it turns out that the issue is, in large part...people. Inefficient workflows can hold companies back from getting the full value of their AI implementations.

For example, data scientists can face challenges getting the resources and data they need to build machine learning models. They may have trouble collaborating with their teammates. And they have many different open source tools to manage, while application developers sometimes need to entirely recode models that data scientists develop before they can embed them into their applications.

With a growing list of open source AI tools, IT ends up spending more time supporting the data science teams by continuously updating their work environments. This issue is compounded by limited standardization across how data science teams like to work.

Finally, senior executives might not be able to visualize the full potential of their companys AI investments. Consequently, they dont lend enough sponsorship and resources to creating the collaborative and integrated ecosystem required for AI to be successful.

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What is Artificial Intelligence (AI)? | Oracle

The impact of artificial intelligence on human society and …

Tzu Chi Med J. 2020 Oct-Dec; 32(4): 339343.

Department of Medical Sociology and Social Work, College of Medicine, Chung Shan Medical University, Taichung, Taiwan

Department of Medical Sociology and Social Work, College of Medicine, Chung Shan Medical University, Taichung, Taiwan

Received 2019 Dec 19; Revised 2020 Jan 30; Accepted 2020 Apr 9.

This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

Artificial intelligence (AI), known by some as the industrial revolution (IR) 4.0, is going to change not only the way we do things, how we relate to others, but also what we know about ourselves. This article will first examine what AI is, discuss its impact on industrial, social, and economic changes on humankind in the 21st century, and then propose a set of principles for AI bioethics. The IR1.0, the IR of the 18th century, impelled a huge social change without directly complicating human relationships. Modern AI, however, has a tremendous impact on how we do things and also the ways we relate to one another. Facing this challenge, new principles of AI bioethics must be considered and developed to provide guidelines for the AI technology to observe so that the world will be benefited by the progress of this new intelligence.

KEYWORDS: Artificial intelligence, Bioethics, Principles of artificial intelligence bioethics

Artificial intelligence (AI) has many different definitions; some see it as the created technology that allows computers and machines to function intelligently. Some see it as the machine that replaces human labor to work for men a more effective and speedier result. Others see it as a system with the ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation [1].

Despite the different definitions, the common understanding of AI is that it is associated with machines and computers to help humankind solve problems and facilitate working processes. In short, it is an intelligence designed by humans and demonstrated by machines. The term AI is used to describe these functions of human-made tool that emulates the cognitive abilities of the natural intelligence of human minds [2].

Along with the rapid development of cybernetic technology in recent years, AI has been seen almost in all our life circles, and some of that may no longer be regarded as AI because it is so common in daily life that we are much used to it such as optical character recognition or the Siri (speech interpretation and recognition interface) of information searching equipment on computer [3].

From the functions and abilities provided by AI, we can distinguish two different types. The first is weak AI, also known as narrow AI that is designed to perform a narrow task, such as facial recognition or Internet Siri search or self-driving car. Many currently existing systems that claim to use AI are likely operating as a weak AI focusing on a narrowly defined specific function. Although this weak AI seems to be helpful to human living, there are still some think weak AI could be dangerous because weak AI could cause disruptions in the electric grid or may damage nuclear power plants when malfunctioned.

The new development of the long-term goal of many researchers is to create strong AI or artificial general intelligence (AGI) which is the speculative intelligence of a machine that has the capacity to understand or learn any intelligent task human being can, thus assisting human to unravel the confronted problem. While narrow AI may outperform humans such as playing chess or solving equations, but its effect is still weak. AGI, however, could outperform humans at nearly every cognitive task.

Strong AI is a different perception of AI that it can be programmed to actually be a human mind, to be intelligent in whatever it is commanded to attempt, even to have perception, beliefs and other cognitive capacities that are normally only ascribed to humans [4].

In summary, we can see these different functions of AI [5,6]:

Automation: What makes a system or process to function automatically

Machine learning and vision: The science of getting a computer to act through deep learning to predict and analyze, and to see through a camera, analog-to-digital conversion and digital signal processing

Natural language processing: The processing of human language by a computer program, such as spam detection and converting instantly a language to another to help humans communicate

Robotics: A field of engineering focusing on the design and manufacturing of cyborgs, the so-called machine man. They are used to perform tasks for human's convenience or something too difficult or dangerous for human to perform and can operate without stopping such as in assembly lines

Self-driving car: Use a combination of computer vision, image recognition amid deep learning to build automated control in a vehicle.

Is AI really needed in human society? It depends. If human opts for a faster and effective way to complete their work and to work constantly without taking a break, yes, it is. However if humankind is satisfied with a natural way of living without excessive desires to conquer the order of nature, it is not. History tells us that human is always looking for something faster, easier, more effective, and convenient to finish the task they work on; therefore, the pressure for further development motivates humankind to look for a new and better way of doing things. Humankind as the homo-sapiens discovered that tools could facilitate many hardships for daily livings and through tools they invented, human could complete the work better, faster, smarter and more effectively. The invention to create new things becomes the incentive of human progress. We enjoy a much easier and more leisurely life today all because of the contribution of technology. The human society has been using the tools since the beginning of civilization, and human progress depends on it. The human kind living in the 21st century did not have to work as hard as their forefathers in previous times because they have new machines to work for them. It is all good and should be all right for these AI but a warning came in early 20th century as the human-technology kept developing that Aldous Huxley warned in his book Brave New World that human might step into a world in which we are creating a monster or a super human with the development of genetic technology.

Besides, up-to-dated AI is breaking into healthcare industry too by assisting doctors to diagnose, finding the sources of diseases, suggesting various ways of treatment performing surgery and also predicting if the illness is life-threatening [7]. A recent study by surgeons at the Children's National Medical Center in Washington successfully demonstrated surgery with an autonomous robot. The team supervised the robot to perform soft-tissue surgery, stitch together a pig's bowel, and the robot finished the job better than a human surgeon, the team claimed [8,9]. It demonstrates robotically-assisted surgery can overcome the limitations of pre-existing minimally-invasive surgical procedures and to enhance the capacities of surgeons performing open surgery.

Above all, we see the high-profile examples of AI including autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art, playing games (such as Chess or Go), search engines (such as Google search), online assistants (such as Siri), image recognition in photographs, spam filtering, predicting flight delaysetc. All these have made human life much easier and convenient that we are so used to them and take them for granted. AI has become indispensable, although it is not absolutely needed without it our world will be in chaos in many ways today.

Questions have been asked: With the progressive development of AI, human labor will no longer be needed as everything can be done mechanically. Will humans become lazier and eventually degrade to the stage that we return to our primitive form of being? The process of evolution takes eons to develop, so we will not notice the backsliding of humankind. However how about if the AI becomes so powerful that it can program itself to be in charge and disobey the order given by its master, the humankind?

Let us see the negative impact the AI will have on human society [10,11]:

A huge social change that disrupts the way we live in the human community will occur. Humankind has to be industrious to make their living, but with the service of AI, we can just program the machine to do a thing for us without even lifting a tool. Human closeness will be gradually diminishing as AI will replace the need for people to meet face to face for idea exchange. AI will stand in between people as the personal gathering will no longer be needed for communication

Unemployment is the next because many works will be replaced by machinery. Today, many automobile assembly lines have been filled with machineries and robots, forcing traditional workers to lose their jobs. Even in supermarket, the store clerks will not be needed anymore as the digital device can take over human labor

Wealth inequality will be created as the investors of AI will take up the major share of the earnings. The gap between the rich and the poor will be widened. The so-called M shape wealth distribution will be more obvious

New issues surface not only in a social sense but also in AI itself as the AI being trained and learned how to operate the given task can eventually take off to the stage that human has no control, thus creating un-anticipated problems and consequences. It refers to AI's capacity after being loaded with all needed algorithm may automatically function on its own course ignoring the command given by the human controller

The human masters who create AI may invent something that is racial bias or egocentrically oriented to harm certain people or things. For instance, the United Nations has voted to limit the spread of nucleus power in fear of its indiscriminative use to destroying humankind or targeting on certain races or region to achieve the goal of domination. AI is possible to target certain race or some programmed objects to accomplish the command of destruction by the programmers, thus creating world disaster.

There are, however, many positive impacts on humans as well, especially in the field of healthcare. AI gives computers the capacity to learn, reason, and apply logic. Scientists, medical researchers, clinicians, mathematicians, and engineers, when working together, can design an AI that is aimed at medical diagnosis and treatments, thus offering reliable and safe systems of health-care delivery. As health professors and medical researchers endeavor to find new and efficient ways of treating diseases, not only the digital computer can assist in analyzing, robotic systems can also be created to do some delicate medical procedures with precision. Here, we see the contribution of AI to health care [7,11]:

IBM's Watson computer has been used to diagnose with the fascinating result. Loading the data to the computer will instantly get AI's diagnosis. AI can also provide various ways of treatment for physicians to consider. The procedure is something like this: To load the digital results of physical examination to the computer that will consider all possibilities and automatically diagnose whether or not the patient suffers from some deficiencies and illness and even suggest various kinds of available treatment.

Pets are recommended to senior citizens to ease their tension and reduce blood pressure, anxiety, loneliness, and increase social interaction. Now cyborgs have been suggested to accompany those lonely old folks, even to help do some house chores. Therapeutic robots and the socially assistive robot technology help improve the quality of life for seniors and physically challenged [12].

Human error at workforce is inevitable and often costly, the greater the level of fatigue, the higher the risk of errors occurring. Al technology, however, does not suffer from fatigue or emotional distraction. It saves errors and can accomplish the duty faster and more accurately.

AI-based surgical procedures have been available for people to choose. Although this AI still needs to be operated by the health professionals, it can complete the work with less damage to the body. The da Vinci surgical system, a robotic technology allowing surgeons to perform minimally invasive procedures, is available in most of the hospitals now. These systems enable a degree of precision and accuracy far greater than the procedures done manually. The less invasive the surgery, the less trauma it will occur and less blood loss, less anxiety of the patients.

The first computed tomography scanners were introduced in 1971. The first magnetic resonance imaging (MRI) scan of the human body took place in 1977. By the early 2000s, cardiac MRI, body MRI, and fetal imaging, became routine. The search continues for new algorithms to detect specific diseases as well as to analyze the results of scans [9]. All those are the contribution of the technology of AI.

The virtual presence technology can enable a distant diagnosis of the diseases. The patient does not have to leave his/her bed but using a remote presence robot, doctors can check the patients without actually being there. Health professionals can move around and interact almost as effectively as if they were present. This allows specialists to assist patients who are unable to travel.

Despite all the positive promises that AI provides, human experts, however, are still essential and necessary to design, program, and operate the AI from any unpredictable error from occurring. Beth Kindig, a San Francisco-based technology analyst with more than a decade of experience in analyzing private and public technology companies, published a free newsletter indicating that although AI has a potential promise for better medical diagnosis, human experts are still needed to avoid the misclassification of unknown diseases because AI is not omnipotent to solve all problems for human kinds. There are times when AI meets an impasse, and to carry on its mission, it may just proceed indiscriminately, ending in creating more problems. Thus vigilant watch of AI's function cannot be neglected. This reminder is known as physician-in-the-loop [13].

The question of an ethical AI consequently was brought up by Elizabeth Gibney in her article published in Nature to caution any bias and possible societal harm [14]. The Neural Information processing Systems (NeurIPS) conference in Vancouver Canada in 2020 brought up the ethical controversies of the application of AI technology, such as in predictive policing or facial recognition, that due to bias algorithms can result in hurting the vulnerable population [14]. For instance, the NeurIPS can be programmed to target certain race or decree as the probable suspect of crime or trouble makers.

Bioethics is a discipline that focuses on the relationship among living beings. Bioethics accentuates the good and the right in biospheres and can be categorized into at least three areas, the bioethics in health settings that is the relationship between physicians and patients, the bioethics in social settings that is the relationship among humankind and the bioethics in environmental settings that is the relationship between man and nature including animal ethics, land ethics, ecological ethicsetc. All these are concerned about relationships within and among natural existences.

As AI arises, human has a new challenge in terms of establishing a relationship toward something that is not natural in its own right. Bioethics normally discusses the relationship within natural existences, either humankind or his environment, that are parts of natural phenomena. But now men have to deal with something that is human-made, artificial and unnatural, namely AI. Human has created many things yet never has human had to think of how to ethically relate to his own creation. AI by itself is without feeling or personality. AI engineers have realized the importance of giving the AI ability to discern so that it will avoid any deviated activities causing unintended harm. From this perspective, we understand that AI can have a negative impact on humans and society; thus, a bioethics of AI becomes important to make sure that AI will not take off on its own by deviating from its originally designated purpose.

Stephen Hawking warned early in 2014 that the development of full AI could spell the end of the human race. He said that once humans develop AI, it may take off on its own and redesign itself at an ever-increasing rate [15]. Humans, who are limited by slow biological evolution, could not compete and would be superseded. In his book Superintelligence, Nick Bostrom gives an argument that AI will pose a threat to humankind. He argues that sufficiently intelligent AI can exhibit convergent behavior such as acquiring resources or protecting itself from being shut down, and it might harm humanity [16].

The question isdo we have to think of bioethics for the human's own created product that bears no bio-vitality? Can a machine have a mind, consciousness, and mental state in exactly the same sense that human beings do? Can a machine be sentient and thus deserve certain rights? Can a machine intentionally cause harm? Regulations must be contemplated as a bioethical mandate for AI production.

Studies have shown that AI can reflect the very prejudices humans have tried to overcome. As AI becomes truly ubiquitous, it has a tremendous potential to positively impact all manner of life, from industry to employment to health care and even security. Addressing the risks associated with the technology, Janosch Delcker, Politico Europe's AI correspondent, said: I don't think AI will ever be free of bias, at least not as long as we stick to machine learning as we know it today,. What's crucially important, I believe, is to recognize that those biases exist and that policymakers try to mitigate them [17]. The High-Level Expert Group on AI of the European Union presented Ethics Guidelines for Trustworthy AI in 2019 that suggested AI systems must be accountable, explainable, and unbiased. Three emphases are given:

Lawful-respecting all applicable laws and regulations

Ethical-respecting ethical principles and values

Robust-being adaptive, reliable, fair, and trustworthy from a technical perspective while taking into account its social environment [18].

Seven requirements are recommended [18]:

AI should not trample on human autonomy. People should not be manipulated or coerced by AI systems, and humans should be able to intervene or oversee every decision that the software makes

AI should be secure and accurate. It should not be easily compromised by external attacks, and it should be reasonably reliable

Personal data collected by AI systems should be secure and private. It should not be accessible to just anyone, and it should not be easily stolen

Data and algorithms used to create an AI system should be accessible, and the decisions made by the software should be understood and traced by human beings. In other words, operators should be able to explain the decisions their AI systems make

Services provided by AI should be available to all, regardless of age, gender, race, or other characteristics. Similarly, systems should not be biased along these lines

AI systems should be sustainable (i.e., they should be ecologically responsible) and enhance positive social change

AI systems should be auditable and covered by existing protections for corporate whistleblowers. The negative impacts of systems should be acknowledged and reported in advance.

From these guidelines, we can suggest that future AI must be equipped with human sensibility or AI humanities. To accomplish this, AI researchers, manufacturers, and all industries must bear in mind that technology is to serve not to manipulate humans and his society. Bostrom and Judkowsky listed responsibility, transparency, auditability, incorruptibility, and predictability [19] as criteria for the computerized society to think about.

Nathan Strout, a reporter at Space and Intelligence System at Easter University, USA, reported just recently that the intelligence community is developing its own AI ethics. The Pentagon made announced in February 2020 that it is in the process of adopting principles for using AI as the guidelines for the department to follow while developing new AI tools and AI-enabled technologies. Ben Huebner, chief of the Office of Director of National Intelligence's Civil Liberties, Privacy, and Transparency Office, said that We're going to need to ensure that we have transparency and accountability in these structures as we use them. They have to be secure and resilient [20]. Two themes have been suggested for the AI community to think more about: Explainability and interpretability. Explainability is the concept of understanding how the analytic works, while interpretability is being able to understand a particular result produced by an analytic [20].

All the principles suggested by scholars for AI bioethics are well-brought-up. I gather from different bioethical principles in all the related fields of bioethics to suggest four principles here for consideration to guide the future development of the AI technology. We however must bear in mind that the main attention should still be placed on human because AI after all has been designed and manufactured by human. AI proceeds to its work according to its algorithm. AI itself cannot empathize nor have the ability to discern good from evil and may commit mistakes in processes. All the ethical quality of AI depends on the human designers; therefore, it is an AI bioethics and at the same time, a trans-bioethics that abridge human and material worlds. Here are the principles:

Beneficence: Beneficence means doing good, and here it refers to the purpose and functions of AI should benefit the whole human life, society and universe. Any AI that will perform any destructive work on bio-universe, including all life forms, must be avoided and forbidden. The AI scientists must understand that reason of developing this technology has no other purpose but to benefit human society as a whole not for any individual personal gain. It should be altruistic, not egocentric in nature

Value-upholding: This refers to AI's congruence to social values, in other words, universal values that govern the order of the natural world must be observed. AI cannot elevate to the height above social and moral norms and must be bias-free. The scientific and technological developments must be for the enhancement of human well-being that is the chief value AI must hold dearly as it progresses further

Lucidity: AI must be transparent without hiding any secret agenda. It has to be easily comprehensible, detectable, incorruptible, and perceivable. AI technology should be made available for public auditing, testing and review, and subject to accountability standards In high-stakes settings like diagnosing cancer from radiologic images, an algorithm that can't explain its work may pose an unacceptable risk. Thus, explainability and interpretability are absolutely required

Accountability: AI designers and developers must bear in mind they carry a heavy responsibility on their shoulders of the outcome and impact of AI on whole human society and the universe. They must be accountable for whatever they manufacture and create.

AI is here to stay in our world and we must try to enforce the AI bioethics of beneficence, value upholding, lucidity and accountability. Since AI is without a soul as it is, its bioethics must be transcendental to bridge the shortcoming of AI's inability to empathize. AI is a reality of the world. We must take note of what Joseph Weizenbaum, a pioneer of AI, said that we must not let computers make important decisions for us because AI as a machine will never possess human qualities such as compassion and wisdom to morally discern and judge [10]. Bioethics is not a matter of calculation but a process of conscientization. Although AI designers can up-load all information, data, and programmed to AI to function as a human being, it is still a machine and a tool. AI will always remain as AI without having authentic human feelings and the capacity to commiserate. Therefore, AI technology must be progressed with extreme caution. As Von der Leyen said in White Paper on AI A European approach to excellence and trust: AI must serve people, and therefore, AI must always comply with people's rights. High-risk AI. That potentially interferes with people's rights has to be tested and certified before it reaches our single market [21].

Nil.

There are no conflicts of interest.

12. Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care published by Skills for Care. [Last accessed on 2019 Aug 15]. Available from: wwwskillsforcareorguk .

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The impact of artificial intelligence on human society and ...